Serialized Form

Package edu.cmu.tetrad.algcomparison

Class edu.cmu.tetrad.algcomparison.Comparison

class Comparison extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

comparisonGraph

Comparison.ComparisonGraph comparisonGraph

The comparison graph type.

dataPath

String dataPath

The data path.

graphTypeUsed

boolean[] graphTypeUsed

The graph type used.

knowledge

Knowledge knowledge

Represents a variable for storing knowledge.

parallelism

int parallelism

The number of threads to use.

resultsPath

String resultsPath

The result path.

saveCPDAGs

boolean saveCPDAGs

Whether to save the CPDAGs.

saveData

boolean saveData

Whether to save the data.

saveGraphs

boolean saveGraphs

Whether to save the graphs.

savePags

boolean savePags

Whether to save the PAGs.

setAlgorithmKnowledge

boolean setAlgorithmKnowledge

True if knowledge should be set on the algorithms (if supplied).

showUtilities

boolean showUtilities

Whether to show the utility calculations.

sortByUtility

boolean sortByUtility

Whether to sort by utility.

tabDelimitedTables

boolean tabDelimitedTables

Indicates whether the tables are tab-delimited.

Package edu.cmu.tetrad.algcomparison.algorithm

Class edu.cmu.tetrad.algcomparison.algorithm.AbstractBootstrapAlgorithm

class AbstractBootstrapAlgorithm extends Object implements Serializable

Serialized Fields

count

int count

Bootstrap count, printed out to track bootstraps.

Class edu.cmu.tetrad.algcomparison.algorithm.AbstractMultiBootstrapAlgorithm

class AbstractMultiBootstrapAlgorithm extends AbstractBootstrapAlgorithm implements Serializable

Serialized Fields

count

int count

Bootstrap count, printed out to track bootstraps.

Class edu.cmu.tetrad.algcomparison.algorithm.Algorithms

class Algorithms extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

algorithms

List<Algorithm> algorithms

The list of algorithm.

Class edu.cmu.tetrad.algcomparison.algorithm.ExternalAlgorithm

class ExternalAlgorithm extends Object implements Serializable

Serialized Fields

path

String path

The path to the external graph.

simIndex

int simIndex

The index of the simulation.

simulation

Simulation simulation

The simulation.

usedParameters

List<String> usedParameters

The parameters used in the search.

Class edu.cmu.tetrad.algcomparison.algorithm.FirstInflection

class FirstInflection extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

high

double high

The high value for the parameter.

increment

double increment

The increment for the parameter.

low

double low

The low value for the parameter.

parameter

String parameter

The parameter to vary.

Class edu.cmu.tetrad.algcomparison.algorithm.StabilitySelection

class StabilitySelection extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the resample searches.

Class edu.cmu.tetrad.algcomparison.algorithm.StARS

class StARS extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to tune.

high

double high

The high value for the parameter.

low

double low

The low value for the parameter.

parameter

String parameter

The parameter to vary.

Package edu.cmu.tetrad.algcomparison.algorithm.continuous.dag

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Dagma

class Dagma extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.DirectLingam

class DirectLingam extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Fask

class Fask extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.FaskOrig

class FaskOrig extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

Deprecated.

The algorithm.

externalGraph

Graph externalGraph

Deprecated.

The external graph.

knowledge

Knowledge knowledge

Deprecated.

The knowledge.

score

ScoreWrapper score

Deprecated.

The score to use.

test

IndependenceWrapper test

Deprecated.

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingam

class IcaLingam extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

bHat

Matrix bHat

The B-Hat matrix found by the most recent search.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.IcaLingD

class IcaLingD extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

stableBHats

List<Matrix> stableBHats

The B-Hat matrices of the stable graphs.

stableGraphs

List<Graph> stableGraphs

The stable graphs found by the most recent search.

unstableBHats

List<Matrix> unstableBHats

The B-Hat matrices of the unstable graphs.

unstableGraphs

List<Graph> unstableGraphs

The unstable graphs found by the most recent search.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.Lingam

class Lingam extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

bHat

Matrix bHat

The bHat variable represents the estimated B matrix generated by the algorithm. The B matrix is a matrix that encodes the causal relationships between the variables in the data set. The bHat variable is implemented as an instance of the Matrix class from the Tetrad library. The Matrix class provides methods for creating and manipulating matrices.

The bHat variable is a private member of the IcaLingam class and is accessible only within the class itself. It is initialized as an empty matrix during the construction of an instance of the IcaLingam algorithm.

To retrieve the estimated B matrix generated by the algorithm, use the getBHat() method. This method returns a reference to the bHat variable, allowing access to the estimated B matrix.

Class edu.cmu.tetrad.algcomparison.algorithm.continuous.dag.LingD

class LingD extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

stableBHats

List<Matrix> stableBHats

A list of stable B matrices generated by the algorithm.

See Also:

• Matrix

stableGraphs

List<Graph> stableGraphs

The stableGraphs variable represents a list of stable graphs generated by the algorithm. A stable graph is a directed graph that satisfies certain criteria and is considered to be a valid result of the algorithm. The list is implemented using the ArrayList class from the Java Collections Framework. The elements in the list are of type Graph, which represents a directed graph.

The stableGraphs variable is a private member of the IcaLingD class and is accessible only within the class itself. It is initialized as an empty list during the construction of an instance of the IcaLingD algorithm.

To retrieve the list of stable graphs generated by the algorithm, use the getStableGraphs() method. This method returns a reference to the stableGraphs variable, allowing access to the list of stable graphs.

unstableBHats

List<Matrix> unstableBHats

Represents a list of unstable B matrices generated by the algorithm.

unstableGraphs

List<Graph> unstableGraphs

Private variable to store a list of unstable graphs.

This variable is used in the IcaLingD class to store a list of unstable graphs generated by the algorithm.

See Also:

• LingD

Package edu.cmu.tetrad.algcomparison.algorithm.multi

Class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskConcatenated

class FaskConcatenated extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskPool

class FaskPool extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

externalGraphAlgorithm

Algorithm externalGraphAlgorithm

Optional algorithm supplying the external graphs (in the GUI, the source graph of a parent graph box, wrapped in a SingleGraphAlg). Run once per dataset, so that each dataset contributes its own graph. Null when no source graph is supplied, in which case the adjacency search selected by FASK_POOL_ADJACENCY runs as before.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.FaskVote

class FaskVote extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

externalGraphAlgorithm

Algorithm externalGraphAlgorithm

Optional algorithm supplying the external graph (in the GUI, the source graph of a parent graph box, wrapped in a SingleGraphAlg). Null when no source graph is supplied, in which case the adjacency search selected by FASK_POOL_ADJACENCY runs as before.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.FciIod

class FciIod extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

Whether to exclude selection bias, captured from the parameters at search time and used to construct the comparison graph.

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.FgesConcatenated

class FgesConcatenated extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

compareToTrue

boolean compareToTrue

True if the result should be compared to the true graph, false if to the CPDAG of the true graph.

externalGraph

Algorithm externalGraph

The external graph.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.Images

class Images extends AbstractMultiBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesBoss

class ImagesBoss extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.ImagesFges

class ImagesFges extends AbstractMultiBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.multi.Ion

class Ion extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

score

ScoreWrapper score

The score to use for the per-dataset BFCI searches.

test

IndependenceWrapper test

The independence test to use for the per-dataset BFCI searches.

Package edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Boss

class Boss extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossCdnodScore

class BossCdnodScore extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

1L

Serialized Fields

knowledge

Knowledge knowledge

Represents the knowledge configuration for the BossCdnodScore class. This field holds an instance of the Knowledge class, which is typically used to define constraints, background information, or domain expertise relevant to the operations performed by the containing class. The Knowledge object may be utilized during the processing of graphs or algorithms, particularly to enforce specific structural or causal constraints on the data model. Its state can be set or modified via relevant methods in the containing class.

score

ScoreWrapper score

The score field represents an instance of ScoreWrapper used to evaluate or measure the performance or accuracy of specific processes in the containing class. This field encapsulates functionality for calculating scores, describing the scoring process, and interacting with the data models and parameters required for scoring. It plays a critical role in driving the behavior of the associated algorithms or methods.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossTopK

class BossTopK extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.BossTrekMimic

class BossTrekMimic extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

inputNames

Set<String> inputNames

Deprecated.

Optional observed variables known to be inputs to the latent structure. Stored by name so they remain stable across node replacement.

knowledge

Knowledge knowledge

Deprecated.

Background knowledge.

outputNames

Set<String> outputNames

Deprecated.

Optional observed variables known to be outputs from the latent structure. Stored by name so they remain stable across node replacement.

test

IndependenceWrapper test

Deprecated.

Independence wrapper used for metadata only.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cam

class Cam extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

1L

Serialized Fields

knowledge

Knowledge knowledge

Represents the knowledge associated with the Cam class. This field is used to store domain-specific background knowledge that may influence the behavior of the implemented search algorithm within this class. It facilitates incorporating prior knowledge into the algorithm's process.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cdnod

class Cdnod extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge object encapsulating domain-specific information for the CD-NOD algorithm.

test

IndependenceWrapper test

The independence test wrapper used by the CD-NOD algorithm.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.CdnodBoss

class CdnodBoss extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

1L

Serialized Fields

knowledge

Knowledge knowledge

Background knowledge; Tier-0 variables are treated as context variables.

score

ScoreWrapper score

The score wrapper supplying the score for the BOSS backbone.

test

IndependenceWrapper test

The independence wrapper supplying the CI test for sepset derivation in the collider-orientation step.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.CdnodPag

class CdnodPag extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Encapsulates prior knowledge constraints to be used during the execution of the algorithm. It defines any structural assumptions or constraints about the data or model, such as forbidden or required edges.

This field can be set and retrieved via the corresponding accessor methods.

score

ScoreWrapper score

Represents an instance of ScoreWrapper used within the Cdnod class. This field is utilized for scoring the generated graphs and evaluating their quality based on the provided implementation.

test

IndependenceWrapper test

Represents an instance of IndependenceWrapper used within the Cdnod class. This field is utilized for performing independence tests and configuring algorithm-specific behaviors based on the provided implementation.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cpc

class Cpc extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Cstar

class Cstar extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

records

LinkedList<Cstar.Record> records

The records.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fas

class Fas extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Fges

class Fges extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.FgesMb

class FgesMb extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

targets

List<Node> targets

The targets.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Flop

class Flop extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Grasp

class Grasp extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.IsFges

class IsFges extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

1L

Serialized Fields

knowledge

Knowledge knowledge

Represents the prior knowledge constraints used by the algorithm. This object manages structural knowledge such as required edges, forbidden edges, and other constraints that guide the search process in the algorithm. Should also contain a test dataset. Needed for reflection.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pc

class Pc extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcAr

class PcAr extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcd

class Pcd extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMax

class PcMax extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.PcMb

class PcMb extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

targets

List<Node> targets

The targets.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Pcmci

class Pcmci extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Represents the instance of Knowledge associated with the PCMCI algorithm. This variable contains domain-specific causal information that can guide or constrain the search process in the PCMCI causal discovery algorithm.

The Knowledge object can store both prior knowledge and structure constraints, including forbidden and required edges in the causal graph.

It is used by methods to retrieve or set domain-specific knowledge to influence the behavior and outcomes of the algorithm.

test

IndependenceWrapper test

An instance of IndependenceWrapper used to perform independence tests and provide associated functionality such as obtaining descriptions, data type, and required parameters specific to the test. This serves as the core element for determining conditional independence in the enclosing Pcmci algorithm.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.RestrictedBoss

class RestrictedBoss extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.SingleGraphAlg

class SingleGraphAlg extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

graph

Graph graph

The graph.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Sp

class Sp extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.Tgin

class Tgin extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

inputNames

Set<String> inputNames

Deprecated.

Optional observed variables known to be inputs to the latent structure. Stored by name so they remain stable across node replacement.

knowledge

Knowledge knowledge

Deprecated.

Background knowledge.

outputNames

Set<String> outputNames

Deprecated.

Optional observed variables known to be outputs from the latent structure. Stored by name so they remain stable across node replacement.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.TrekMimic

class TrekMimic extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

inputNames

Set<String> inputNames

Optional observed variables known to be inputs to the latent structure. Stored by name so they remain stable across node replacement.

knowledge

Knowledge knowledge

Background knowledge.

outputNames

Set<String> outputNames

Optional observed variables known to be outputs from the latent structure. Stored by name so they remain stable across node replacement.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag.TwoStep

class TwoStep extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

2L

Serialized Fields

knowledge

Knowledge knowledge

Deprecated.

The knowledge object, maintained for API compatibility. It is not used directly in the implementation of this class but may serve as a placeholder to ensure parity with other similar APIs or extensions. This variable can be accessed or modified through the provided getter and setter methods.

Package edu.cmu.tetrad.algcomparison.algorithm.oracle.pag

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Bfci

class Bfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

A boolean variable that determines whether to exclude selection bias in the BOSS-FCI algorithm. When set to true, the algorithm applies adjustments to handle or mitigate selection bias in the data, potentially improving causal inference in scenarios impacted by such biases. The default value is false, meaning selection bias is not excluded.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BfciBryan

class BfciBryan extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

Whether to exclude selection bias in the comparison graph.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BfciBryanScore

class BfciBryanScore extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

Whether to exclude selection bias in the comparison graph.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BfciC

class BfciC extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

A boolean variable that determines whether to exclude selection bias in the BOSS-FCI algorithm. When set to true, the algorithm applies adjustments to handle or mitigate selection bias in the data, potentially improving causal inference in scenarios impacted by such biases. The default value is false, meaning selection bias is not excluded.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BfciD

class BfciD extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

A boolean variable that determines whether to exclude selection bias in the BOSS-FCI algorithm. When set to true, the algorithm applies adjustments to handle or mitigate selection bias in the data, potentially improving causal inference in scenarios impacted by such biases. The default value is false, meaning selection bias is not excluded.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BfciScoreCheck

class BfciScoreCheck extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

excludeSelectionBias

boolean excludeSelectionBias

Whether to exclude selection bias.

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossCcd

class BossCcd extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Background knowledge (forbidden directed edges only).

score

ScoreWrapper score

The score to use (BOSS phase).

test

IndependenceWrapper test

The independence test to use (CCD phase).

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossFci

class BossFci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.BossPod

class BossPod extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Ccd

class Ccd extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Represents the knowledge structure associated with the CCD (Cyclic Causal Discovery) algorithm. The knowledge object typically holds domain-specific constraints or background knowledge that is used to guide the search process in the algorithm.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cfci

class Cfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Cpw

class Cpw extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

test

IndependenceWrapper test

Independence test wrapper.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Dm

class Dm extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Background knowledge.

test

IndependenceWrapper test

The independence-wrapper used to construct the test.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.DmFcit

class DmFcit extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.DmPc

class DmPc extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fci

class Fci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciCyclicPw

class FciCyclicPw extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

test

IndependenceWrapper test

Independence test wrapper (same as FCI wrapper).

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FciMax

class FciMax extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Fcit

class Fcit extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FcitMagMarkov

class FcitMagMarkov extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FcitMarkov

class FcitMarkov extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FcitSl

class FcitSl extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FcitSlScoreCheck

class FcitSlScoreCheck extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.FcitZm

class FcitZm extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gfci

class Gfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GfciOld

class GfciOld extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Gmas

class Gmas extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.GraspFci

class GraspFci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Icd

class Icd extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

1L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.IsGfci

class IsGfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

test

IndependenceWrapper test

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvBossExperimental

class LvBossExperimental extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.LvHeuristic

class LvHeuristic extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSampleRfci

class PagSampleRfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.PagSamplingRfci

class PagSamplingRfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge

test

IndependenceWrapper test

The probabilistic test

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.Rfci

class Rfci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Represents the knowledge variable. This variable stores the knowledge associated with the given algorithm. The type of the variable is Knowledge.

See Also:

• Knowledge

test

IndependenceWrapper test

The independence test to use.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.RfciBsc

class RfciBsc extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

Knowledge

test

IndependenceWrapper test

Independence test; must the ProbabilisticTest.

Class edu.cmu.tetrad.algcomparison.algorithm.oracle.pag.SpFci

class SpFci extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

score

ScoreWrapper score

The score to use.

test

IndependenceWrapper test

The independence wrapper used for testing the independence between variables in a dataset.

Package edu.cmu.tetrad.algcomparison.algorithm.other

Class edu.cmu.tetrad.algcomparison.algorithm.other.FactorAnalysis

class FactorAnalysis extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.algorithm.other.Glasso

class Glasso extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.algorithm.other.MimbuildBollen

class MimbuildBollen extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Represents a specification for blocks used in the Mimbuild Bollen algorithm. This variable manages the configuration of block-related information, such as the grouping of variables into blocks or other related structural considerations.

Class edu.cmu.tetrad.algcomparison.algorithm.other.MimbuildPca

class MimbuildPca extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Represents the block specification used within the MimbuildPca algorithm. This variable defines the structure of blocks and the block variables to be used during the execution of the PCA-based search for latent structure.

Class edu.cmu.tetrad.algcomparison.algorithm.other.PythonGin

class PythonGin extends Object implements Serializable

serialVersionUID:

1L

Class edu.cmu.tetrad.algcomparison.algorithm.other.Rlcd

class Rlcd extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The background knowledge passed to the search.

Package edu.cmu.tetrad.algcomparison.algorithm.pairwise

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.FaskPw

class FaskPw extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R1

class R1 extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R2

class R2 extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.R3

class R3 extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Rskew

class Rskew extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.RskewE

class RskewE extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Skew

class Skew extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.SkewE

class SkewE extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Class edu.cmu.tetrad.algcomparison.algorithm.pairwise.Tanh

class Tanh extends AbstractBootstrapAlgorithm implements Serializable

serialVersionUID:

23L

Serialized Fields

algorithm

Algorithm algorithm

The algorithm to use for the initial graph.

externalGraph

Graph externalGraph

The external graph.

Package edu.cmu.tetrad.algcomparison.graph

Class edu.cmu.tetrad.algcomparison.graph.Cyclic

class Cyclic extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.ErdosRenyi

class ErdosRenyi extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.RandomForward

class RandomForward extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.RandomMim

class RandomMim extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.RandomMimic

class RandomMimic extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.RandomSingleFactorMim

class RandomSingleFactorMim extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.RandomTwoFactorMim

class RandomTwoFactorMim extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.ScaleFree

class ScaleFree extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.graph.SingleGraph

class SingleGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

graph

Graph graph

The graph to be used.

Package edu.cmu.tetrad.algcomparison.independence

Class edu.cmu.tetrad.algcomparison.independence.BasisExpandedGcm

class BasisExpandedGcm extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.BasisFunctionBlocksIndTest

class BasisFunctionBlocksIndTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.BasisFunctionLrt

class BasisFunctionLrt extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.BlocksIndTest

class BlocksIndTest extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Deprecated.

Stores the specification for blocks used in the BlocksIndTest. This object determines how data is divided into blocks for statistical independence testing.

Class edu.cmu.tetrad.algcomparison.independence.BlocksIndTestLemma10

class BlocksIndTestLemma10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Deprecated.

Represents the specification for block structures required in the "Blocks Test Lemma 10" independence test implementation. This variable holds the configuration or details defining the nature of the blocks to be used in the test.

Class edu.cmu.tetrad.algcomparison.independence.BlocksIndTestTs

class BlocksIndTestTs extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Represents the specification for block structures required in the "Blocks Test Lemma 10" independence test implementation. This variable holds the configuration or details defining the nature of the blocks to be used in the test.

Class edu.cmu.tetrad.algcomparison.independence.CciTest

class CciTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.ChiSquare

class ChiSquare extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.ClFisherZPython

class ClFisherZPython extends Object implements Serializable

serialVersionUID:

24L

Class edu.cmu.tetrad.algcomparison.independence.ClKciPython

class ClKciPython extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.ClRcitPython

class ClRcitPython extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.ConditionalGaussianLrt

class ConditionalGaussianLrt extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Cord

class Cord extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.DegenerateGaussianLrt

class DegenerateGaussianLrt extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.DgBicTest

class DgBicTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.EquivalenceTest

class EquivalenceTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.FfCi

class FfCi extends Object implements Serializable

serialVersionUID:

24L

Class edu.cmu.tetrad.algcomparison.independence.FfCiContinuous

class FfCiContinuous extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.FisherZ

class FisherZ extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Gcm

class Gcm extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Gin

class Gin extends Object implements Serializable

serialVersionUID:

1L

Class edu.cmu.tetrad.algcomparison.independence.GSquare

class GSquare extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Kci

class Kci extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.MinimaxCITest

class MinimaxCITest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.MSeparationTest

class MSeparationTest extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

graph

Graph graph

The true graph.

Class edu.cmu.tetrad.algcomparison.independence.MultinomialLogisticRegressionWald

class MultinomialLogisticRegressionWald extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Mvplrt

class Mvplrt extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.PoissonBicTest

class PoissonBicTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.ProbabilisticTest

class ProbabilisticTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.RankIndependenceTestLemma10Singletons

class RankIndependenceTestLemma10Singletons extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.RankIndependenceTestTs

class RankIndependenceTestTs extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.RankIndependenceTestTsSingletons

class RankIndependenceTestTsSingletons extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.RankIndependenceTestWilkesSingletons

class RankIndependenceTestWilkesSingletons extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.Rcit

class Rcit extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.SemBicTest

class SemBicTest extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.StratifiedRank

class StratifiedRank extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.TrekSeparationBlocksIndependence

class TrekSeparationBlocksIndependence extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.independence.TRffLrTest

class TRffLrTest extends Object implements Serializable

serialVersionUID:

1L

Package edu.cmu.tetrad.algcomparison.score

Class edu.cmu.tetrad.algcomparison.score.BasisFunctionBgeScore

class BasisFunctionBgeScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScore

class BasisFunctionBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.BasisFunctionBicScoreTabular

class BasisFunctionBicScoreTabular extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.BdeuScore

class BdeuScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.BfBlocksBicScore

class BfBlocksBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Specifies the block structure for the score calculation. Used to organize variables into predefined blocks for analysis.

Class edu.cmu.tetrad.algcomparison.score.BgeScore

class BgeScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.BlocksBicScore

class BlocksBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockSpec

BlockSpec blockSpec

Specifies the block structure for the score calculation. Used to organize variables into predefined blocks for analysis.

Class edu.cmu.tetrad.algcomparison.score.ConditionalGaussianBicScore

class ConditionalGaussianBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBgeScore

class DegenerateGaussianBgeScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.DegenerateGaussianBicScore

class DegenerateGaussianBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.DiscreteBicScore

class DiscreteBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.EbicScore

class EbicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.FfMl

class FfMl extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Deserializes the object from the given ObjectInputStream. Resets the transient dataSet field to null to ensure that it is properly reinitialized after deserialization.

Parameters:

in - the ObjectInputStream from which the object is read

Throws:

IOException - if an I/O error occurs while reading the stream

ClassNotFoundException - if the class of a serialized object cannot be found

Class edu.cmu.tetrad.algcomparison.score.FfMlContinuous

class FfMlContinuous extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.GicScores

class GicScores extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.HeavyTailSemBicScore

class HeavyTailSemBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.HuangMarginalLikelihoodScore

class HuangMarginalLikelihoodScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.InstanceAugmentedSemBicScoreWrapper

class InstanceAugmentedSemBicScoreWrapper extends Object implements Serializable

Serialized Fields

knowledge

Knowledge knowledge

Represents the prior background knowledge utilized in the scoring or analysis process. This variable holds constraints or assumptions about the data, which guide or restrict the structure learning or model evaluation.

Class edu.cmu.tetrad.algcomparison.score.IsBDeuScoreWrapper

class IsBDeuScoreWrapper extends Object implements Serializable

Serialized Fields

knowledge

Knowledge knowledge

Represents a knowledge structure used within the IsBDeuScoreWrapper class. This variable stores an instance of the Knowledge class and is utilized to manage and represent domain-specific constraints or prior information in the context of scoring operations.

Class edu.cmu.tetrad.algcomparison.score.KcvBicScore

class KcvBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.KernelMarginalLikelihoodScore

class KernelMarginalLikelihoodScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.MagDgBicScore

class MagDgBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.MSepScore

class MSepScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

graph

Graph graph

The graph.

Class edu.cmu.tetrad.algcomparison.score.MVPBicScore

class MVPBicScore extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.score.PoissonPriorScore

class PoissonPriorScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.RankBicScore

class RankBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.RffBicScore

class RffBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.SemBicScore

class SemBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Class edu.cmu.tetrad.algcomparison.score.TRffBicScore

class TRffBicScore extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Handles the deserialization of a TRffBicScore object. This ensures that the object is properly restored from its serialized form. During the deserialization process, the underlying dataset reference is reset to null to enforce reinitialization after the object is loaded.

Parameters:

in - the ObjectInputStream from which the object is being deserialized. This stream contains the serialized representation of the object.

Throws:

IOException - if an I/O error occurs during deserialization.

ClassNotFoundException - if the class of a serialized object cannot be found.

Class edu.cmu.tetrad.algcomparison.score.ZhangShenBoundScore

class ZhangShenBoundScore extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataModel dataSet

The data set.

Package edu.cmu.tetrad.algcomparison.simulation

Class edu.cmu.tetrad.algcomparison.simulation.AdditiveNoiseSimulation

class AdditiveNoiseSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator.

Class edu.cmu.tetrad.algcomparison.simulation.BayesNetSimulation

class BayesNetSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

im

BayesIm im

The Bayes IM.

ims

List<BayesIm> ims

The Bayes IMs.

pm

BayesPm pm

The Bayes PM.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.ConditionalGaussianSimulation

class ConditionalGaussianSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

coefHigh

double coefHigh

The high coefficient.

coefLow

double coefLow

The low coefficient.

coefSymmetric

boolean coefSymmetric

Whether coefficients should be drawn equally from positive or negative values.

dataSets

List<DataSet> dataSets

The data sets.

dataType

DataType dataType

The data type.

graphs

List<Graph> graphs

The graphs.

meanHigh

double meanHigh

The high mean for variables.

meanLow

double meanLow

The low mean for variables.

randomGraph

RandomGraph randomGraph

The random graph.

shuffledOrder

List<Node> shuffledOrder

The shuffled order.

varHigh

double varHigh

The high variance.

varLow

double varLow

The low variance.

Class edu.cmu.tetrad.algcomparison.simulation.DaoSimulation

class DaoSimulation extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

dataSets

List<DataSet> dataSets

List of generated data sets; may be empty.

graphs

List<Graph> graphs

List of generated DAGs; may be empty.

randomGraph

RandomGraph randomGraph

Source of true DAGs; must not be null.

Class edu.cmu.tetrad.algcomparison.simulation.DesignedExperimentSimulation

class DesignedExperimentSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

configurationStarts

List<int[]> configurationStarts

Per simulation index, the starting row of each configuration block in the emitted data (a single all-rows block when deSortByConfiguration is off).

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator (ignored; kept for factory compatibility).

Class edu.cmu.tetrad.algcomparison.simulation.GeneralAdditiveModel

class GeneralAdditiveModel extends Object implements Serializable

serialVersionUID:

24L

Serialized Fields

dataSets

List<DataSet> dataSets

A collection of data models used within the General Additive Model (GAM).

This field stores a list of DataSet objects, which represent the datasets generated or used during the execution of the model. The list is initialized as an empty ArrayList and is populated through data generation, simulation, or external interaction with the class.

graphs

List<Graph> graphs

A list of Graph objects used within the General Additive Model.

This list serves as a central collection of graphs, where each graph represents a distinct structure used for data modeling or simulations. Graphs stored in this list are typically generated or modified through various operations within the model.

randomGraph

RandomGraph randomGraph

Represents the random graph used within the General Additive Model (GAM). This graph serves as the foundation for data generation, simulations, and various dependent operations in the model.

The associated RandomGraph instance dictates the structure and characteristics of the graph, and its description and parameters are utilized in configuring the model.

This variable is immutable and must be initialized at the time of object construction, ensuring consistency and preventing unintended modifications to the underlying graph.

Class edu.cmu.tetrad.algcomparison.simulation.GeneralNoiseSimulation

class GeneralNoiseSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator.

Class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulation

class GeneralSemSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

im

GeneralizedSemIm im

Represents the GeneralizedSemIm object used for simulation.

ims

List<GeneralizedSemIm> ims

The SEM IMs.

pm

GeneralizedSemPm pm

The SEM PM.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.GeneralSemSimulationSpecial1

class GeneralSemSimulationSpecial1 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The graphs.

graphs

List<Graph> graphs

The data sets.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.GpSemSimulation

class GpSemSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.HybridCgSimulation

class HybridCgSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

im

HybridCgModel.HybridCgIm im

Represents a SemIm object used for simulation.

ims

List<HybridCgModel.HybridCgIm> ims

The SEM IMs.

pm

HybridCgModel.HybridCgPm pm

The SEM PM.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.LeeHastieSimulation

class LeeHastieSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

dataType

DataType dataType

The data type.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph.

shuffledOrder

List<Node> shuffledOrder

The shuffled order.

Class edu.cmu.tetrad.algcomparison.simulation.LgMnarSimulation

class LgMnarSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator.

Class edu.cmu.tetrad.algcomparison.simulation.LinearFisherModel

class LinearFisherModel extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph.

shocks

List<DataModel> shocks

The shocks.

Class edu.cmu.tetrad.algcomparison.simulation.LinearSineSimulation

class LinearSineSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

betaHigh

double betaHigh

The beta high.

betaLow

double betaLow

The beta low.

dataSets

List<DataSet> dataSets

The data sets.

dataType

DataType dataType

The data type.

gammaHigh

double gammaHigh

The gamma high.

gammaLow

double gammaLow

The gamma low.

graphs

List<Graph> graphs

The graphs.

interceptHigh

double interceptHigh

The intercept high.

interceptLow

double interceptLow

The intercept low.

linearHigh

double linearHigh

The linear high.

linearLow

double linearLow

The linear low.

randomGraph

RandomGraph randomGraph

The random graph.

shuffledOrder

List<Node> shuffledOrder

The shuffled order.

varHigh

double varHigh

The var high.

varLow

double varLow

The var low.

Class edu.cmu.tetrad.algcomparison.simulation.NonGaussianSemSimulation

class NonGaussianSemSimulation extends SemSimulation implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.simulation.NonlinearFunctionsOfLinear

class NonlinearFunctionsOfLinear extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator.

Class edu.cmu.tetrad.algcomparison.simulation.ObservationalStudySimulation

class ObservationalStudySimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

contemporaneousGraphs

List<Graph> contemporaneousGraphs

The contemporaneous summary graphs (equal to the true graphs in non-serial mode).

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The true graphs (DAGs, or TimeLagGraphs in serial mode).

randomGraph

RandomGraph randomGraph

The random graph generator (ignored; kept for factory compatibility).

subjectStarts

List<int[]> subjectStarts

Per-run subject start row indices.

Class edu.cmu.tetrad.algcomparison.simulation.PostnonlinearSem

class PostnonlinearSem extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The random graph generator.

Class edu.cmu.tetrad.algcomparison.simulation.SemSimulation

class SemSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

im

SemIm im

Represents a SemIm object used for simulation.

ims

List<SemIm> ims

The SEM IMs.

pm

SemPm pm

The SEM PM.

randomGraph

RandomGraph randomGraph

The random graph.

Class edu.cmu.tetrad.algcomparison.simulation.SemThenDiscretize

class SemThenDiscretize extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

dataType

DataType dataType

The data type.

graphs

List<Graph> graphs

The data sets.

randomGraph

RandomGraph randomGraph

The random graph.

shuffledOrder

List<Node> shuffledOrder

The shuffled order.

Class edu.cmu.tetrad.algcomparison.simulation.Simulations

class Simulations extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

simulations

List<Simulation> simulations

The simulations.

Class edu.cmu.tetrad.algcomparison.simulation.SingleDatasetSimulation

class SingleDatasetSimulation extends Object implements Serializable

Serialized Fields

dataSet

DataSet dataSet

The dataSet variable represents a single supplied data set.

Class edu.cmu.tetrad.algcomparison.simulation.StandardizedSemSimulation

class StandardizedSemSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

pm

SemPm pm

The SEM PM.

randomGraph

RandomGraph randomGraph

The random graph.

standardizedIm

StandardizedSemIm standardizedIm

The SEM IM.

Class edu.cmu.tetrad.algcomparison.simulation.TimeSeriesSemSimulation

class TimeSeriesSemSimulation extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The data sets.

knowledge

Knowledge knowledge

The expanded knowledge derived from the lagged graph structure, and optionally augmented with the expanded within-lag knowledge. This is what gets stamped onto each dataset and passed to the search algorithm.

randomGraph

RandomGraph randomGraph

The random graph.

withinLagKnowledge

Knowledge withinLagKnowledge

Within-lag knowledge supplied by the user over base variable names (no lag suffix). May be null. If non-null, this is expanded across all lags in createData and merged into the structural knowledge.

Class edu.cmu.tetrad.algcomparison.simulation.TrainedDagModel

class TrainedDagModel extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

DataSet data

The shocks.

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

randomGraph

RandomGraph randomGraph

The graph.

Package edu.cmu.tetrad.algcomparison.statistic

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFn

class AdjacencyFn extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFp

class AdjacencyFp extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyFpr

class AdjacencyFpr extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyPrecision

class AdjacencyPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyRecall

class AdjacencyRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTn

class AdjacencyTn extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTp

class AdjacencyTp extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AdjacencyTpr

class AdjacencyTpr extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AncestorF1

class AncestorF1 extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AncestorPrecision

class AncestorPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AncestorRecall

class AncestorRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AncestralPrecision

class AncestralPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AncestralRecall

class AncestralRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFn

class ArrowheadFn extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFp

class ArrowheadFp extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadFpr

class ArrowheadFpr extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecision

class ArrowheadPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadPrecisionCommonEdges

class ArrowheadPrecisionCommonEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecall

class ArrowheadRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadRecallCommonEdges

class ArrowheadRecallCommonEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTn

class ArrowheadTn extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ArrowheadTp

class ArrowheadTp extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeEst

class AverageDegreeEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.AverageDegreeTrue

class AverageDegreeTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BicDiff

class BicDiff extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

precomputeCovariances

boolean precomputeCovariances

Whether to precompute covariances.

Class edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord

class BicDiffPerRecord extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

precomputeCovariances

boolean precomputeCovariances

Whether to precompute covariances.

Class edu.cmu.tetrad.algcomparison.statistic.BicEst

class BicEst extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

precomputeCovariances

boolean precomputeCovariances

Whether to precompute covariances.

Class edu.cmu.tetrad.algcomparison.statistic.BicTrue

class BicTrue extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

precomputeCovariances

boolean precomputeCovariances

Whether to precompute covariances.

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedEst

class BidirectedEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedFP

class BidirectedFP extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentExistsLatentCommonCause

class BidirectedLatentExistsLatentCommonCause extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedLatentPrecision

class BidirectedLatentPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedPrecision

class BidirectedPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedRecall

class BidirectedRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedTP

class BidirectedTP extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.BidirectedTrue

class BidirectedTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CirclePrecision

class CirclePrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CircleRecall

class CircleRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalseNegativeBidirected

class CommonAncestorFalseNegativeBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorFalsePositiveBidirected

class CommonAncestorFalsePositiveBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CommonAncestorTruePositiveBidirected

class CommonAncestorTruePositiveBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CommonMeasuredAncestorRecallBidirected

class CommonMeasuredAncestorRecallBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.CorrectSkeleton

class CorrectSkeleton extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathPrecision

class DefiniteDirectedPathPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.DefiniteDirectedPathRecall

class DefiniteDirectedPathRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.DensityEst

class DensityEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.DensityTrue

class DensityTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ElapsedCpuTime

class ElapsedCpuTime extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.F1Adj

class F1Adj extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.F1All

class F1All extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.F1Arrow

class F1Arrow extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.F1Circle

class F1Circle extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.F1Tail

class F1Tail extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.FalseNegativesAdjacencies

class FalseNegativesAdjacencies extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.FalsePositiveAdjacencies

class FalsePositiveAdjacencies extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.FBetaAdj

class FBetaAdj extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

beta

double beta

The beta parameter.

Class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderAlternative

class FractionDependentUnderAlternative extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The significance level for the independence tests.

Class edu.cmu.tetrad.algcomparison.statistic.FractionDependentUnderNull

class FractionDependentUnderNull extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The significance level.

Class edu.cmu.tetrad.algcomparison.statistic.GraphExactlyRight

class GraphExactlyRight extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.IdaAverageSquaredDistance

class IdaAverageSquaredDistance extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

semIm

SemIm semIm

The true SEM IM. This stat can only be used if the true SEM IM is known.

Class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMaxSquaredDiffEstTrue

class IdaCheckAvgMaxSquaredDiffEstTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgMinSquaredDiffEstTrue

class IdaCheckAvgMinSquaredDiffEstTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.IdaCheckAvgSquaredDifference

class IdaCheckAvgSquaredDifference extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.IdaMaximumSquaredDifference

class IdaMaximumSquaredDifference extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

semIm

SemIm semIm

The true SEM IM. This stat can only be used if the true SEM IM is known.

Class edu.cmu.tetrad.algcomparison.statistic.IdaMinimumSquaredDifference

class IdaMinimumSquaredDifference extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

semIm

SemIm semIm

The true SEM IM. This stat can only be used if the true SEM IM is known.

Class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst

class ImpliedArrowOrientationRatioEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ImpliedArrowOrientationRatioEst2

class ImpliedArrowOrientationRatioEst2 extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ImpliedOrientationRatioEst

class ImpliedOrientationRatioEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ImpliesLegalMag

class ImpliesLegalMag extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.KnowledgeSatisfied

class KnowledgeSatisfied extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The `knowledge` variable represents a knowledge object.

This variable is a private member of the `KnowledgeSatisfied` class, which implements the `Statistic` and `HasKnowledge` interfaces. It is used to measure whether the provided knowledge is satisfied for the estimated graph.

It is initially set to `null`.

See Also:

• KnowledgeSatisfied
• Statistic
• AcceptsKnowledge

Class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalseNegativeBidirected

class LatentCommonAncestorFalseNegativeBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorFalsePositiveBidirected

class LatentCommonAncestorFalsePositiveBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorRecallBidirected

class LatentCommonAncestorRecallBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LatentCommonAncestorTruePositiveBidirected

class LatentCommonAncestorTruePositiveBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LegalCpdag

class LegalCpdag extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LegalPag

class LegalPag extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.LocalGraphPrecision

class LocalGraphPrecision extends Object implements Serializable

Class edu.cmu.tetrad.algcomparison.statistic.LocalGraphRecall

class LocalGraphRecall extends Object implements Serializable

Class edu.cmu.tetrad.algcomparison.statistic.MagCgScore

class MagCgScore extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.MagDgScore

class MagDgScore extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.MagSemScore

class MagSemScore extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPasses

class MarkovCheckAdPasses extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Represents the type of conditioning set to be used in Markov checks for evaluating independence relationships in a graph or data set. The conditioning set determines which variables are conditioned on during independence tests, influencing the nature and scope of the independence facts being tested.

This variable works in conjunction with IndependenceWrapper to perform statistical evaluations related to Markov property testing. Its specific type is defined by the ConditioningSetType enum, which provides various options such as GLOBAL_MARKOV, LOCAL_MARKOV, and others, each corresponding to a particular approach to selecting the conditioning set.

independenceWrapper

IndependenceWrapper independenceWrapper

Provides an interface to independence tests for evaluating conditional independence relationships in a data set. It is used as a dependency for statistical computations and Markov checks within the containing class.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckAdPasses instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAdPassesBestOf10

class MarkovCheckAdPassesBestOf10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Represents the type of conditioning set employed during the Markov check for evaluating conditional independence relationships in a graph. The selected conditioning set type influences how variables are conditioned upon in independence tests.

This variable is used to configure the scope and basis of the tests, providing flexibility to support various methodologies, such as local Markov properties or global Markov properties.

Possible values are enumerated in the ConditioningSetType enum and include options such as GLOBAL_MARKOV, LOCAL_MARKOV, PARENTS_AND_NEIGHBORS, and others.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of IndependenceWrapper used to evaluate conditional independence relationships in a given data set. This object encapsulates the logic required for independence tests along with relevant parameters and descriptions of the data type being tested.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckAdPassesBestOf10 instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingP

class MarkovCheckAndersonDarlingP extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set employed during Markov checks. This variable determines how variables are conditioned in independence tests and is represented by the ConditioningSetType enumeration. The chosen conditioning set type dictates the methodology used to test for independence relationships in the context of graphical models.

independenceWrapper

IndependenceWrapper independenceWrapper

Encapsulates and facilitates the execution of independence tests on datasets with specific configurations. This variable serves as a key component in determining dependencies or independencies among variables in statistical models, especially during the computation of the Markov check and Anderson-Darling P-value.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckAndersonDarlingP instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckAndersonDarlingPBestOf10

class MarkovCheckAndersonDarlingPBestOf10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used for Markov checks in statistical tests. This variable determines how the independence tests are conducted, influencing the set of variables considered to condition on when evaluating independence relationships in a graph.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of the IndependenceWrapper interface, which provides methods to assess statistical independence relationships in datasets. This wrapper is used in conjunction with various tests to evaluate dependencies and supports the execution of algorithms that rely on independence test results. Its specific implementation determines the behavior of the test and the parameters required for its execution.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckAndersonDarlingPBestOf10 instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialP

class MarkovCheckBinomialP extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used for the Markov check in statistical evaluations. The conditioning set determines which variables are conditioned on when testing for independence or dependence among variables in a graph. It impacts the way independence facts are tested and interpreted, particularly in the context of causal modeling. Different types of conditioning sets correspond to distinct independence testing strategies, such as global or local tests.

independenceWrapper

IndependenceWrapper independenceWrapper

Encapsulates an instance of an IndependenceWrapper, which provides methods to perform independence tests, retrieve test descriptions, manage data type requirements, and obtain associated parameters. This variable is central in conducting independence testing within the context of statistical evaluation for algorithms.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckBinomialP instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckBinomialPBestOf10

class MarkovCheckBinomialPBestOf10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used in the Markov check to assess conditional independence relationships within the graph. The conditioning set determines the subset of variables to condition on during independence testing, which impacts how independence and dependence relationships are evaluated based on the causal structure of the graph.

This variable is integral to configuring the statistical computation of independence facts in the MarkovCheckBinomialPBestOf10 class.

independenceWrapper

IndependenceWrapper independenceWrapper

Wrapper for independence tests used in statistical computations. This field represents the specific implementation of the IndependenceWrapper interface that supplies methods for determining independence between variables, describing the type of data involved, and retrieving test parameters.

It is used to calculate statistical measures and perform conditional independence tests based on provided data and parameters.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckFdrCutoffP

class MarkovCheckFdrCutoffP extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used in the Markov check. Determines how independence tests are conducted based on the graph structure by conditioning on a specific set of variables. The choice of the conditioning set type impacts the assessment of conditional independence and derived dependencies.

This field is immutable and initialized during the instantiation of the MarkovCheckKolmogorovSmirnoffP class.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of the IndependenceWrapper interface that encapsulates the independence test logic. Used for generating and applying independence tests within the context of statistical calculations. The independenceWrapper field supplies a way to determine whether variables in data are independent, conditional on a provided conditioning set, and produces relevant test results.

mcParameters

Parameters mcParameters

Encapsulates the configuration parameters used for the Markov check calculation, particularly in determining whether the p-values for the estimated graph are distributed as U(0, 1). These parameters influence the behavior and outcomes during the statistical analysis process. This field is immutable and is initialized during the construction of the MarkovCheckKolmogorovSmirnoffP object. The settings within mcParameters are utilized during the execution of methods related to Markov check processes.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckFractionDependentH0

class MarkovCheckFractionDependentH0 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

The type of conditioning set used within the MarkovCheckFractionDependentH0 class to specify the approach for determining conditioning sets in statistical independence tests during Markov checks. This variable defines the strategy applied for selecting the conditioning sets, impacting how independence facts are tested and inferred. The selected ConditioningSetType determines how the contextual dependencies or independencies in a graph model are analyzed, as described by the available options in the ConditioningSetType enumeration.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of IndependenceWrapper that provides access to independence tests and related functionality for evaluating statistical independence in a dataset. Used as part of the Markov check process to determine if the p-values for an estimated graph are uniformly distributed.

mcParameters

Parameters mcParameters

The parameters associated with the MarkovCheckFractionDependentH0 instance, encapsulating configuration details and settings relevant to the Markov check process.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckFractionDependentH1

class MarkovCheckFractionDependentH1 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Represents the type of conditioning set used in the Markov check. This variable determines the strategy for selecting the set of variables to condition on when performing independence tests. The choice of conditioning set type impacts the interpretation of the independence or dependence facts discovered during the analysis.

independenceWrapper

IndependenceWrapper independenceWrapper

Encapsulates an independence test and provides methods for accessing it based on the given data model and parameters. This wrapper abstracts different types of independence tests, making them accessible through a unified interface.

mcParameters

Parameters mcParameters

Represents the configuration parameters for the Markov check, which are used to control various aspects of the Markov independence tests and statistical calculations performed within the MarkovCheckFractionDependentH1 class. This field is immutable and set at the time of object construction, ensuring that the parameters remain consistent throughout the lifespan of the MarkovCheckFractionDependentH1 instance.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffP

class MarkovCheckKolmogorovSmirnoffP extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used in the Markov check. Determines how independence tests are conducted based on the graph structure by conditioning on a specific set of variables. The choice of the conditioning set type impacts the assessment of conditional independence and derived dependencies.

This field is immutable and initialized during the instantiation of the MarkovCheckKolmogorovSmirnoffP class.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of the IndependenceWrapper interface that encapsulates the independence test logic. Used for generating and applying independence tests within the context of statistical calculations. The independenceWrapper field supplies a way to determine whether variables in data are independent, conditional on a provided conditioning set, and produces relevant test results.

mcParameters

Parameters mcParameters

Encapsulates the configuration parameters used for the Markov check calculation, particularly in determining whether the p-values for the estimated graph are distributed as U(0, 1). These parameters influence the behavior and outcomes during the statistical analysis process. This field is immutable and is initialized during the construction of the MarkovCheckKolmogorovSmirnoffP object. The settings within mcParameters are utilized during the execution of methods related to Markov check processes.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKolmogorovSmirnoffPBestOf10

class MarkovCheckKolmogorovSmirnoffPBestOf10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set to be used for the Markov check in calculations. The conditioning set determines how independence facts are tested and is defined by the ConditioningSetType enum.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of the IndependenceWrapper interface used for conducting independence tests. This variable is critical for determining whether variables in a dataset are independent based on specified conditions. It enables the evaluation of statistical independence necessary for assessing the structure of causal graphs and for the execution of Markov-related validation checks.

IndependenceWrapper provides methods for obtaining independence tests, retrieving test descriptions, handling parameter requirements, and verifying the compatibility of data types used for independence assessments. This interface serves as a foundational component in algorithms implementing statistical structure learning and evaluation.

mcParameters

Parameters mcParameters

Represents a configuration parameter object used to control and provide settings for performing Markov checks, including calculations and evaluations of statistical measures such as the Kolmogorov-Smirnoff P value. This field is immutable and encapsulates the required parameters for conducting specific computations within the MarkovCheckKolmogorovSmirnoffPBestOf10 class.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPasses

class MarkovCheckKsPasses extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used to evaluate conditional independence relationships during statistical tests in the Markov check process.

The conditioning set determines the set of variables used in independence tests, impacting the assumptions made and the results of the Markov check. Different ConditioningSetTypes correspond to varying definitions of variable dependencies and independence implied by the graph, ranging from global to local contexts.

This variable plays a critical role in selecting the appropriate conditioning technique to align with the statistical model under analysis.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of IndependenceWrapper used to encapsulate an independence testing algorithm for evaluating conditional independence relationships in statistical models.

The IndependenceWrapper is responsible for performing independence tests, retrieving test descriptions, determining the required data types, and managing algorithm-specific parameters.

mcParameters

Parameters mcParameters

Parameters used for configuring the Markov check process in the MarkovCheckKsPasses class. This variable encapsulates the necessary configuration options and metadata needed to perform the Kolmogorov-Smirnoff tests to validate whether the p-values of the estimated graph adhere to a uniform distribution (U(0, 1)). It is passed during the construction of the MarkovCheckKsPasses instance.

Class edu.cmu.tetrad.algcomparison.statistic.MarkovCheckKsPassesBestOf10

class MarkovCheckKsPassesBestOf10 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Represents the type of conditioning set used during the Markov checks in the context of statistical dependence testing. It specifies how variables are conditioned upon during independence tests and directly influences the results of the Markov checks. The type is defined by the ConditioningSetType enumeration, which includes various strategies for defining the conditioning set, such as GLOBAL_MARKOV, LOCAL_MARKOV, or MARKOV_BLANKET among others. This field is immutable and must be set during the initialization of the object.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of IndependenceWrapper used to encapsulate and perform independence tests on the dataset with specific configurations. This variable is intended to facilitate independence testing within the context of Markov check calculations and other statistical operations in the enclosing class.

mcParameters

Parameters mcParameters

Represents the parameter configuration used for performing the Markov checks in the MarkovCheckKsPassesBestOf10 class. It encapsulates various settings and options that control how the statistical tests are executed. This field is immutable and must be initialized during the construction of the MarkovCheckKsPassesBestOf10 instance. It plays a critical role in determining the behavior of the Kolmogorov-Smirnov tests and other related operations in the context of the Markov checks.

Class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrAdj

class MathewsCorrAdj extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.MathewsCorrArrow

class MathewsCorrArrow extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.Maximal

class Maximal extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.MaximalityCondition

class MaximalityCondition extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.McGetNumTestsH0

class McGetNumTestsH0 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set to use when calculating independence tests within the context of the Markov check. This variable determines the approach used for conditioning on variables in the graph during statistical analysis.

independenceWrapper

IndependenceWrapper independenceWrapper

Encapsulates an implementation of the IndependenceWrapper interface used to perform independence tests on a dataset. This wrapper provides the ability to retrieve a specific implementation of the IndependenceTest depending on the given data model and test parameters.

The independenceWrapper is used to integrate independence testing logic into classes that require customizable or interchangeable independence test implementations, such as the determination of conditional independence relationships in statistical models or algorithms.

mcParameters

Parameters mcParameters

Represents the set of parameters used specifically within the context of the Markov check process in the McGetNumTestsH0 class. These parameters influence the configuration and execution of independence tests and associated computations.

Class edu.cmu.tetrad.algcomparison.statistic.McGetNumTestsH1

class McGetNumTestsH1 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

conditioningSetType

ConditioningSetType conditioningSetType

Specifies the type of conditioning set used in the Markov check for evaluating independence or dependence relationships. This variable is associated with the configuration of the independence tests and determines how the conditioning set is constructed based on the selected type from the ConditioningSetType enum. The conditioning set influences the statistical properties of the independence tests performed during Markov checks.

independenceWrapper

IndependenceWrapper independenceWrapper

An instance of the IndependenceWrapper interface used to perform independence tests in the context of statistical computations and graph evaluations. It provides the necessary methods to retrieve and configure independence tests, as well as to obtain a description of the specific independence testing algorithm being employed.

mcParameters

Parameters mcParameters

Represents the parameters required to perform computations within the context of a Markov check for evaluating whether the p-values for an estimated graph conform to a uniform distribution U(0, 1). This variable encapsulates configurations and settings for the associated computation, providing necessary input to methods and algorithms that require parameterized adjustments.

Class edu.cmu.tetrad.algcomparison.statistic.NoAlmostCyclicPathsCondition

class NoAlmostCyclicPathsCondition extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NoCyclicPathsCondition

class NoCyclicPathsCondition extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesPrecision

class NodesInCyclesPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NodesInCyclesRecall

class NodesInCyclesRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NonancestorPrecision

class NonancestorPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NonancestorRecall

class NonancestorRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NoPotentiallyDirectedF1

class NoPotentiallyDirectedF1 extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedPrecision

class NoSemidirectedPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NoSemidirectedRecall

class NoSemidirectedRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumAmbiguousTriples

class NumAmbiguousTriples extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsEst

class NumberArrowsEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberArrowsNotInUnshieldedCollidersEst

class NumberArrowsNotInUnshieldedCollidersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberCollidersEst

class NumberCollidersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesEst

class NumberEdgesEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInCollidersEst

class NumberEdgesInCollidersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesInUnshieldedCollidersEst

class NumberEdgesInUnshieldedCollidersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberEdgesTrue

class NumberEdgesTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesEst

class NumberOfEdgesEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberOfEdgesTrue

class NumberOfEdgesTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberTailsEst

class NumberTailsEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumberUnshieldedCollidersEst

class NumberUnshieldedCollidersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedBothNonancestorAncestor

class NumBidirectedBothNonancestorAncestor extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesEst

class NumBidirectedEdgesEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumBidirectedEdgesTrue

class NumBidirectedEdgesTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumColoredDD

class NumColoredDD extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumColoredNL

class NumColoredNL extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumColoredPD

class NumColoredPD extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumColoredPL

class NumColoredPL extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCommonMeasuredAncestorBidirected

class NumCommonMeasuredAncestorBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDefiniteDirectedEdgeAncestors

class NumCompatibleDefiniteDirectedEdgeAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeConfounded

class NumCompatibleDirectedEdgeConfounded extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleDirectedEdgeNonAncestors

class NumCompatibleDirectedEdgeNonAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleEdges

class NumCompatibleEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeAncestors

class NumCompatiblePossiblyDirectedEdgeAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePossiblyDirectedEdgeNonAncestors

class NumCompatiblePossiblyDirectedEdgeNonAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePotentiallyDirectedEdgeAncestors

class NumCompatiblePotentiallyDirectedEdgeAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatiblePotentiallyDirectedEdgeNonAncestors

class NumCompatiblePotentiallyDirectedEdgeNonAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCompatibleVisibleNonancestors

class NumCompatibleVisibleNonancestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCorrectBidirected

class NumCorrectBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCorrectDDAncestors

class NumCorrectDDAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCorrectPDAncestors

class NumCorrectPDAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCorrectVisibleEdges

class NumCorrectVisibleEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumCoveringAdjacenciesInPag

class NumCoveringAdjacenciesInPag extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyDirected

class NumDefinitelyDirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDefinitelyNotDirectedPaths

class NumDefinitelyNotDirectedPaths extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeAncestors

class NumDirectedEdgeAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeBnaMeasuredCounfounded

class NumDirectedEdgeBnaMeasuredCounfounded extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNoMeasureAncestors

class NumDirectedEdgeNoMeasureAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeNotAncNotRev

class NumDirectedEdgeNotAncNotRev extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdgeReversed

class NumDirectedEdgeReversed extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedEdges

class NumDirectedEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsEst

class NumDirectedPathsEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedPathsTrue

class NumDirectedPathsTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumDirectedShouldBePartiallyDirected

class NumDirectedShouldBePartiallyDirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumEdgeInEstInTrue

class NumEdgeInEstInTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumGenuineAdjacenciesInPag

class NumGenuineAdjacenciesInPag extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectDDAncestors

class NumIncorrectDDAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectPDAncestors

class NumIncorrectPDAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumIncorrectVisibleAncestors

class NumIncorrectVisibleAncestors extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumLatentCommonAncestorBidirected

class NumLatentCommonAncestorBidirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumNondirectedEdges

class NumNondirectedEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumParametersEst

class NumParametersEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumPartiallyOrientedEdges

class NumPartiallyOrientedEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumPotentiallyDirected

class NumPotentiallyDirected extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumUndirectedEdges

class NumUndirectedEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdges

class NumVisibleEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.NumVisibleEdgeTrue

class NumVisibleEdgeTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.OrientationPrecision

class OrientationPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.OrientationRecall

class OrientationRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyPrecision

class PagAdjacencyPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.PagAdjacencyRecall

class PagAdjacencyRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ParameterColumn

class ParameterColumn extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

parameter

String parameter

The name of the parameter to list. If this parameter does not exist, '*' is output.

Class edu.cmu.tetrad.algcomparison.statistic.PercentAmbiguous

class PercentAmbiguous extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.PercentBidirectedEdges

class PercentBidirectedEdges extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedEst

class ProportionSemidirectedPathsNotReversedEst extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.ProportionSemidirectedPathsNotReversedTrue

class ProportionSemidirectedPathsNotReversedTrue extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.PvalueDistanceToAlpha

class PvalueDistanceToAlpha extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The significance level for the independence tests.

Class edu.cmu.tetrad.algcomparison.statistic.PvalueUniformityUnderNull

class PvalueUniformityUnderNull extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The significance level for the independence tests.

Class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPathF1

class SemidirectedPathF1 extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.SemidirectedPrecision

class SemidirectedPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.SemidirectedRecall

class SemidirectedRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.Statistics

class Statistics extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

statistics

List<Statistic> statistics

The list of statistics.

weights

Map<Statistic, Double> weights

The utility weights for the statistics.

Class edu.cmu.tetrad.algcomparison.statistic.StructuralHammingDistance

class StructuralHammingDistance extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

compareToCpdag

boolean compareToCpdag

Indicates whether the Structural Hamming Distance (SHD) calculation should be based on the CPDAG (Completed Partially Directed Acyclic Graph) form of the true graph rather than its original PDAG (Partially Directed Acyclic Graph) form. When set to true, the SHD computation compares the estimated graph to the CPDAG of the true graph; otherwise, it compares the estimated graph to the true PDAG.

Class edu.cmu.tetrad.algcomparison.statistic.TailPrecision

class TailPrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TailRecall

class TailRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesArrows

class TrueDagFalseNegativesArrows extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalseNegativesTails

class TrueDagFalseNegativesTails extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveArrow

class TrueDagFalsePositiveArrow extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagFalsePositiveTails

class TrueDagFalsePositiveTails extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionArrow

class TrueDagPrecisionArrow extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagPrecisionTails

class TrueDagPrecisionTails extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallArrows

class TrueDagRecallArrows extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagRecallTails

class TrueDagRecallTails extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveArrow

class TrueDagTruePositiveArrow extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveDirectedPathNonancestor

class TrueDagTruePositiveDirectedPathNonancestor extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TrueDagTruePositiveTails

class TrueDagTruePositiveTails extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalseNegative

class TwoCycleFalseNegative extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TwoCycleFalsePositive

class TwoCycleFalsePositive extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TwoCyclePrecision

class TwoCyclePrecision extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TwoCycleRecall

class TwoCycleRecall extends Object implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.algcomparison.statistic.TwoCycleTruePositive

class TwoCycleTruePositive extends Object implements Serializable

serialVersionUID:

23L

Package edu.cmu.tetrad.algcomparison.utils

Class edu.cmu.tetrad.algcomparison.utils.PooledIndependenceWrapper

class PooledIndependenceWrapper extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

defaultDataSets

List<DataModel> defaultDataSets

A defensive copy of the default data sets used when none have been registered for the calling thread via PooledIndependenceWrapper.setThreadDataSets(List); all pooled data sets must have the same variables by name.

inner

IndependenceWrapper inner

The inner independence wrapper used to construct independence tests for pooled data sets. This wrapper is encapsulated within the PooledIndependenceWrapper to delegate independence testing on individual data sets while maintaining the pooled data operations.

• Responsible for evaluating independence conditional on given inputs.
• Defines the underlying description, data type, and parameters of the test.
• Serves as the core component around which the pooled independence tests are built.

It is required to be non-null when constructing a PooledIndependenceWrapper.

Class edu.cmu.tetrad.algcomparison.utils.PooledScoreWrapper

class PooledScoreWrapper extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

defaultDataSets

List<DataModel> defaultDataSets

A defensive copy of the default data sets used when none have been registered for the calling thread via PooledScoreWrapper.setThreadDataSets(List).

inner

ScoreWrapper inner

Represents the inner score wrapper used to calculate individual scores for each pooled data set. This field is immutable and is utilized to delegate the scoring logic to the underlying implementation of ScoreWrapper. The inner score wrapper is essential for coordinating the scoring process within the pooled context. If the provided score wrapper implements MultiDataSetScoreWrapper, its specific scoring mechanism is utilized. This field is initialized during the construction of the containing PooledScoreWrapper and must not be null. Attempts to construct with a null value result in a NullPointerException.

Package edu.cmu.tetrad.annotation

Class edu.cmu.tetrad.annotation.AnnotatedClass

class AnnotatedClass extends Object implements Serializable

serialVersionUID:

5060798016477163171L

Serialized Fields

annotation

T extends Annotation annotation

AnnotatedClass represents a class along with its associated annotation.

clazz

Class<?> clazz

Represents a Class used as a parameter to an AnnotatedClass object. It is stored as a private final member in the AnnotatedClass class.

Example usage:

AnnotatedClass<MyAnnotation> annotatedClass = new AnnotatedClass<>(MyClass.class, myAnnotation);
Class<?> clazz = annotatedClass.clazz();

See Also:

• AnnotatedClass

Package edu.cmu.tetrad.bayes

Class edu.cmu.tetrad.bayes.ApproximateUpdater

class ApproximateUpdater extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesIm

BayesIm bayesIm

The IM which this updater modifies.

Cannot be null.

counts

int[][] counts

Counts of data points for each variable value.

evidence

Evidence evidence

Stores evidence for all variables.

Cannot be null.

manipulatedBayesIm

BayesIm manipulatedBayesIm

This is the source BayesIm after manipulation; all data simulations should be taken from this.

Class edu.cmu.tetrad.bayes.BayesImProbs

class BayesImProbs extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesIm

BayesIm bayesIm

Represents a variable of the BayesIm class.

variables

List<Node> variables

Represents a list of nodes.

Class edu.cmu.tetrad.bayes.BayesPm

class BayesPm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

dag

Graph dag

The underlying graph that's being parameterized.

Cannot be null.

nodesToVariables

Map<Node, DiscreteVariable> nodesToVariables

The map from nodes to variables.

Cannot be null.

Class edu.cmu.tetrad.bayes.CptMapCounts

class CptMapCounts extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

cellCounts

Map<Integer,Integer> cellCounts

Constructs a new count map, a map from a unique integer index for a particular node to the count for that value, where 0's are not stored.

numColumns

int numColumns

The number of columns in the table.

numRows

int numRows

The number of rows in the table.

priorCount

double priorCount

The prior count for all cells. '0' is maximimum likelihood estimate.

rowCounts

Map<Integer,Integer> rowCounts

Constructs a new row count map, a map from a unique integer index for a particular node to the count for that row, where 0's are not stored.

Class edu.cmu.tetrad.bayes.CptMapProbs

class CptMapProbs extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

map

Map<Integer,Double> map

Constructs a new probability map, a map from a unique integer index for a particular node to the probability of that node taking on that value, where NaN's are not stored.

numColumns

int numColumns

The number of columns in the table.

numRows

int numRows

The number of rows in the table.

Class edu.cmu.tetrad.bayes.DirichletBayesIm

class DirichletBayesIm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesPm

BayesPm bayesPm

The associated Bayes PM model.

nextRowTotal

double nextRowTotal

1.0000 The default row size for randomly creating new rows.

nodes

Node[] nodes

The array of nodes from the graph. Order is important.

parentDims

int[][] parentDims

The array of dimensionality (number of values for each node) for each of the subarrays of 'parents'.

parents

int[][] parents

The list of parents for each node from the graph. Order or nodes corresponds to the order of nodes in 'nodes', and order in subarrays is important.

pseudocounts

double[][][] pseudocounts

The main data structure; stores the values of all of the pseudocounts for the Dirichlet Bayes net of the form row by row, for each node. The first dimension is the node N, in the order of 'nodes'. The second dimension is the row index for the table of parameters associated with node N; the third dimension is the column index. The row index is calculated by the function getRowIndex(int[] values) where 'values' is an array of numerical indices for each of the parent values; the order of the values in this array is the same as the order of node in 'parents'; the value indices are obtained from the Bayes PM for each node. The column is the index of the value of N, where this index is obtained from the Bayes PM. If a pseudocount is -1, that means its value should be filled in manually.

Class edu.cmu.tetrad.bayes.Evidence

class Evidence extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

manipulation

Manipulation manipulation

A manipulation indicating how the bayes Im should be manipulated before updating.

proposition

Proposition proposition

A proposition stating what we know for each variable.

Class edu.cmu.tetrad.bayes.Identifiability

class Identifiability extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesIm

BayesIm bayesIm

The BayesIm which this updater modifies.

debug

boolean debug

The last manipulated BayesIm.

evidence

Evidence evidence

Stores evidence for all variables.

manipulatedBayesIm

BayesIm manipulatedBayesIm

The last manipulated BayesIm.

Class edu.cmu.tetrad.bayes.JunctionTreeInference

class JunctionTreeInference extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

allowedMask

boolean[][] allowedMask

A two-dimensional boolean array representing soft evidence for allowed categories. Each element in the array indicates whether a specific category is allowed for a given variable. A true value signifies that the category is allowed, while false indicates it is disallowed. If allowedMask is null, it implies that all categories are allowed for all variables, imposing no restrictions. This array plays a critical role in influencing probabilistic inference by restricting the possible outcomes for variables during computations.

bayesIm

BayesIm bayesIm

Represents the Bayesian network structure and Conditional Probability Tables (CPTs) used by the JunctionTreeInference class for probabilistic inference. This field encapsulates the Bayesian Interference Model (BayesIm), which provides the structure and parameters of the Bayesian Network, allowing the inference algorithm to compute marginal probabilities, joint probabilities, and conditional probabilities over the variables of the network. The BayesIm is essential for constructing junction trees, assigning factors to cliques, and calibrating the network for efficient exact inference. This field is immutable and instantiated through the constructor of the containing JunctionTreeInference class. All inference-related computations performed within the class rely on the information held by this BayesIm instance.

cachedEvidenceProb

double cachedEvidenceProb

Cached result of the evidence probability computation. This variable stores the computed probability of the observed evidence in the Bayesian network. It is used to avoid redundant calculations when the evidence remains unchanged. The value is initialized to Double.NaN, indicating that the evidence probability has not been computed or that the cached value is invalid. The value is updated during the inference process, particularly when the network is calibrated or the evidence changes.

calibratedDirty

boolean calibratedDirty

Indicates whether the current calibration state of the junction tree is invalid or "dirty." This flag is used to determine if recalibration is needed. It is set to true when any operation invalidates the calibration, such as changes to evidence or modifications to the internal structure of the junction tree. Once recalibration is performed, this flag should be toggled back to false.

card

int[] card

An array representing the cardinalities for each variable in the Bayesian Network. Each element corresponds to the number of distinct possible values (or categories) that the respective variable can take. The index of the array corresponds directly to the variable index in the Bayesian model.

cliqueAssignedFactors

List<List<edu.cmu.tetrad.bayes.JunctionTreeInference.Factor>> cliqueAssignedFactors

A nested list structure where each inner list corresponds to the factors assigned to a specific clique within the junction tree. Each factor encapsulates conditional probability information or evidence for nodes in the Bayesian network. This list is organized to map directly to the cliques in the junction tree, ensuring that each clique is associated with the relevant subset of factors. These factors play a critical role in calibrating the junction tree and performing probabilistic inference.

cliqueNeighbors

List<int[]> cliqueNeighbors

Stores the adjacency lists of clique indices in the junction tree structure. Each element in the list corresponds to a clique, represented as an array of integers where each integer is the index of a neighboring clique. The adjacency lists define the connections between cliques in the tree, enabling traversal and message passing during inference. These connections are crucial for implementing algorithms like the HUGIN algorithm for probabilistic inference. The structure and contents of the adjacency lists are determined during the construction of the junction tree and remain immutable throughout the inference process.

cliques

List<edu.cmu.tetrad.bayes.JunctionTreeInference.Clique> cliques

Represents the collection of cliques used in the Junction Tree algorithm for probabilistic inference. Each clique is a subset of variables selected to satisfy the properties of the Junction Tree. Characteristics: - The cliques are maximal cliques derived from the triangulated moralized graph of the Bayesian network. - Stored as an immutable list and serves as the structural backbone for performing inference operations. - Used in conjunction with separators to manage potential distributions across subproblems.

hardEvidence

int[] hardEvidence

An array representing fixed evidence values for nodes in the Bayesian network. Each element corresponds to a specific node, where: - A value of `-1` indicates no evidence for that particular node. - Any other value represents the fixed evidence for the node, corresponding to a specific category or state. This array is used in the process of probabilistic inference to incorporate known evidence into the calculations performed by the underlying inference algorithm.

n

int n

Represents the total number of variables in the Bayesian network. This value is utilized in various computational processes within the junction tree inference algorithm to manage variable-related operations.

separators

Map<Long, edu.cmu.tetrad.bayes.JunctionTreeInference.Separator> separators

A mapping of separators used in the Junction Tree inference process. Each separator represents the shared variables (separator variables) between two cliques in the Junction Tree structure, facilitating message passing during the inference process. The key of the map is a composite based on the IDs of the minimum and maximum Clique IDs `(minClique, maxClique)`, ensuring consistent and unique referencing for each separator. The corresponding value is an instance of the `Separator` class, which encapsulates the details of the separator, including the IDs of the connected cliques, the shared variables, and any associated message-passing factors.

Class edu.cmu.tetrad.bayes.JunctionTreeUpdater

class JunctionTreeUpdater extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Reads the state of the object from the provided ObjectInputStream. Ensures that necessary fields are not null after deserialization and reconstructs transient fields required for the object's functionality.

Parameters:

s - the ObjectInputStream to read data from.

Throws:

IOException - if an I/O error occurs during reading.

ClassNotFoundException - if a class required for deserialization cannot be found.

NullPointerException - if key fields such as bayesIm or evidence are null after deserialization.

Serialized Fields

bayesIm

BayesIm bayesIm

Represents a Bayesian network instantiation model (BayesIm) that provides properties or methods to define and manipulate a parameterized Bayesian Network. The structure includes conditional probabilities for nodes in the network, defining how they interact and depend on one another. This variable is immutable and is initialized upon declaration.

evidence

Evidence evidence

Stores evidence for all variables (Indexed to SOURCE variable list).

IMPORTANT: This is intentionally NOT defensively copied, matching RowSummingExactUpdater behavior. The UI may mutate Evidence in-place.

manipulatedBayesIm

BayesIm manipulatedBayesIm

Represents a manipulated Bayesian network in the form of a BayesIm. This variable is used to store a version of the network modified based on specific interventions or adjustments. These modifications may involve altering conditional probability tables (CPTs) to reflect the effects of applied changes.

The manipulatedBayesIm is distinct from the original and updated Bayesian networks, as it encapsulates the changes applied to the network state during the manipulation process.

updatedBayesIm

BayesIm updatedBayesIm

Represents the updated Bayesian network model after incorporating the effects of interventions, adjustments, or evidence updates. This field stores a BayesIm instance that contains the recalculated probabilities and structure reflecting the current state of the Bayesian network.

The updated Bayesian network differs from the original network and the manipulated network in that it encapsulates the comprehensive state derived from applying all relevant changes. It is typically used for inference and analysis within the context of Bayesian network operations.

Class edu.cmu.tetrad.bayes.Manipulation

class Manipulation extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

manipulated

boolean[] manipulated

An array indicating whether each variable in turn is manipulated.

variableSource

VariableSource variableSource

The variable source for which this manipulation is defined.

Class edu.cmu.tetrad.bayes.MlBayesIm

class MlBayesIm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesPm

BayesPm bayesPm

The associated Bayes PM model.

cptMapType

MlBayesIm.CptMapType cptMapType

The type of CPT map used to store the probabilities.

nodes

Node[] nodes

The array of nodes from the graph. Order is important.

parentDims

int[][] parentDims

The array of dimensionality (number of categories for each node) for each of the subarrays of 'parents'.

parents

int[][] parents

The list of parents for each node from the graph. Order or nodes corresponds to the order of nodes in 'nodes', and order in subarrays is important.

probMatrices

CptMap[] probMatrices

The array of CPT maps for each node. The index of the node corresponds to the index of the probability map in this array. Replaces the probs array.

probs

double[][][] probs

The main data structure; stores the values of all of the conditional probabilities for the Bayes net of the form P(N=v0 | P1=v1, P2=v2,...). The first dimension is the node N, in the order of 'nodes'. The second dimension is the row index for the table of parameters associated with node N; the third dimension is the column index. The row index is calculated by the function getRowIndex(int[] values) where 'values' is an array of numerical indices for each of the parent values; the order of the values in this array is the same as the order of node in 'parents'; the value indices are obtained from the Bayes PM for each node. The column is the index of the value of N, where this index is obtained from the Bayes PM.

This is kept here for backward compatibility. The new way of storing the probabilities is in the probMatrices array.

Class edu.cmu.tetrad.bayes.MlBayesImObs

class MlBayesImObs extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bayesImObs

BayesIm bayesImObs

BayesIm containing only the observed variables. Only used to 1) construct propositions (mapped from the original allowUnfaithfulness bayesIm) in Identifiability 2) to avoid summing over rows in jpd when only the latent variables have changed values (only sum when all the latent variables have value 0) This is a MlBayesIm instead of a MlBayesImObs because otherwise there will be an infinite loop attempting to creating the MlBayesImObs

bayesImRandomize

BayesIm bayesImRandomize

a regular MlBayesIm used to create randomized CPDs so that the values can be marginalized to a consistent observed jpd

bayesPm

BayesPm bayesPm

The associated Bayes PM model.

jpd

StoredCellProbsObs jpd

joint probability table

nodes

Node[] nodes

The array of nodes from the graph. Order is important.

parentDims

int[][] parentDims

The array of dimensionality (number of categories for each node) for each of the subarrays of 'parents'.

parents

int[][] parents

The list of parents for each node from the graph. Order or nodes corresponds to the order of nodes in 'nodes', and order in subarrays is important.

probs

double[][][] probs

The main data structure; stores the values of all of the conditional probabilities for the Bayes net of the form P(N=v0 | P1=v1, P2=v2,...). The first dimension is the node N, in the order of 'nodes'. The second dimension is the row index for the table of parameters associated with node N; the third dimension is the column index. The row index is calculated by the function getRowIndex(int[] values) where 'values' is an array of numerical indices for each of the parent values; the order of the values in this array is the same as the order of node in 'parents'; the value indices are obtained from the Bayes PM for each node. The column is the index of the value of N, where this index is obtained from the Bayes PM.

Class edu.cmu.tetrad.bayes.Proposition

class Proposition extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

allowedCategories

boolean[][] allowedCategories

An array indicating whether each category for each variable is allowed.

variableSource

VariableSource variableSource

The Bayes IM that this is a proposition for.

Class edu.cmu.tetrad.bayes.RowSummingExactUpdater

class RowSummingExactUpdater extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Deserializes the RowSummingExactUpdater object from the provided input stream. This method ensures that the deserialized object has all mandatory fields non-null.

Parameters:

s - the ObjectInputStream from which the object is read

Throws:

IOException - if an I/O error occurs while reading the stream

ClassNotFoundException - if the class of a serialized object could not be found

NullPointerException - if the deserialized object's bayesIm or evidence fields are null

Serialized Fields

bayesIm

BayesIm bayesIm

The BayesIm which this updater modifies.

bayesImProbs

BayesImProbs bayesImProbs

Calculates probabilities from the manipulated Bayes IM.

evidence

Evidence evidence

Stores evidence for all variables. (Indexed to the SOURCE variable list.)

manipulatedBayesIm

BayesIm manipulatedBayesIm

The last manipulated BayesIm (after do()-surgery).

updatedBayesIm

BayesIm updatedBayesIm

The BayesIm after update, if this was calculated.

Class edu.cmu.tetrad.bayes.StoredCellProbs

class StoredCellProbs extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

parentDims

int[] parentDims

The parent dimensions of the table.

probs

double[] probs

The cell probabilities.

variables

List<Node> variables

The variables for which this table stores cell probabilities.

Class edu.cmu.tetrad.bayes.StoredCellProbsObs

class StoredCellProbsObs extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

parentDims

int[] parentDims

The number of values for each parent.

probs

double[] probs

The probabilities.

variables

List<Node> variables

The variables for which the cell probabilities are stored.

Class edu.cmu.tetrad.bayes.UpdatedBayesIm

class UpdatedBayesIm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - a ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

affectedVars

boolean[] affectedVars

A boolean array that is true at a position if the node at that index is an ancestor or a child of one of the evidence variables.

bayesIm

BayesIm bayesIm

The wrapped BayesIm. Unmodified conditional probability values will be retrieved from here.

changedProbs

double[][][] changedProbs

Stores probs that change with respect to the underlying bayesIm, calculated on the fly.

evidence

Evidence evidence

The evidence updated on.

Class edu.cmu.tetrad.bayes.VariableEliminationInference

class VariableEliminationInference extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

allowedMask

boolean[][] allowedMask

A two-dimensional boolean array used as a mask to represent allowed categories for variables in the Bayesian network. Each row corresponds to a variable, and each column represents a category of that variable. A value of true indicates that the corresponding category is allowed, while false indicates that it is disallowed. The allowedMask is typically manipulated during the inference process to encode constraints such as soft evidence, hard evidence, or query-specific assignments. It serves as a key internal structure for defining and applying these restrictions when computing probabilities or distributions.

bayesIm

BayesIm bayesIm

Represents the BayesIm instance used to perform Bayesian inference within the VariableEliminationInference class. This field encapsulates the structure, parameters, and conditional probability distributions of a Bayesian network. It serves as the core reference for computations involving evidence, marginal probabilities, conditional distributions, and joint probabilities. The BayesIm instance is immutable to ensure consistency during inference operations and is defined at the time of construction.

cachedEvidenceProb

double cachedEvidenceProb

Cached value of the probability of the current evidence (both hard and soft) in the Bayesian Network. This value is used to avoid redundant computations of the evidence probability. Initialized to Double.NaN to indicate that the cache is invalid or the evidence probability has not been computed yet. The cache is managed internally and recomputed by methods that modify or depend on the evidence state, such as setEvidence, setAllowedCategories, or other computational routines involving evidence probabilities.

hardEvidence

int[] hardEvidence

Stores hard evidence for Bayesian network inference. Each index in the array corresponds to a node in the network, and the value at that index represents the observed category for the node. A value of -1 indicates that no hard evidence is set for the corresponding node. This array is immutable and is used as part of the inference process.

normalizerDirty

boolean normalizerDirty

Indicates whether the normalizer value or calculations within the inference process are outdated and need to be recomputed. When set to true, cached results or internal state related to normalization are considered invalid, triggering recomputation where necessary.

Class edu.cmu.tetrad.bayes.VariableEliminationUpdater

class VariableEliminationUpdater extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Reads the state of the object from the provided ObjectInputStream. Ensures that necessary fields are not null after deserialization and reconstructs transient fields required for the object's functionality.

Parameters:

s - the ObjectInputStream to read data from.

Throws:

IOException - if an I/O error occurs during reading.

ClassNotFoundException - if a class required for deserialization cannot be found.

NullPointerException - if key fields such as bayesIm or evidence are null after deserialization.

Serialized Fields

bayesIm

BayesIm bayesIm

Represents a Bayesian network instantiation model (BayesIm) that provides properties or methods to define and manipulate a parameterized Bayesian Network. The structure includes conditional probabilities for nodes in the network, defining how they interact and depend on one another.

This variable is immutable and is initialized upon declaration.

evidence

Evidence evidence

Stores evidence for all variables (Indexed to SOURCE variable list).

IMPORTANT: This is intentionally NOT defensively copied, matching RowSummingExactUpdater behavior. The UI may mutate Evidence in-place.

manipulatedBayesIm

BayesIm manipulatedBayesIm

Represents a manipulated Bayesian network in the form of a BayesIm. This variable is used to store a version of the network modified based on specific interventions or adjustments. These modifications may involve altering conditional probability tables (CPTs) to reflect the effects of applied changes.

The manipulatedBayesIm is distinct from the original and updated Bayesian networks, as it encapsulates the changes applied to the network state during the manipulation process.

updatedBayesIm

BayesIm updatedBayesIm

Represents the updated Bayesian network model after incorporating the effects of interventions, adjustments, or evidence updates. This field stores a BayesIm instance that contains the recalculated probabilities and structure reflecting the current state of the Bayesian network.

The updated Bayesian network differs from the original network and the manipulated network in that it encapsulates the comprehensive state derived from applying all relevant changes. It is typically used for inference and analysis within the context of Bayesian network operations.

Package edu.cmu.tetrad.calculator.expression

Class edu.cmu.tetrad.calculator.expression.AbstractExpressionDescriptor.Signature

class Signature extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

arguments

String[] arguments

The function name.

signature

String signature

The signature string.

Class edu.cmu.tetrad.calculator.expression.ConstantExpression

class ConstantExpression extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

name

String name

The name of the constant or null if there isn't one. Constants with names are things like PI or E.

value

double value

THe value of the expression.

Class edu.cmu.tetrad.calculator.expression.EvaluationExpression

class EvaluationExpression extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

string

String string

The string you are testing the variable against.

variable

VariableExpression variable

The variable part of the expression.

Exception Class edu.cmu.tetrad.calculator.expression.ExpressionInitializationException

class ExpressionInitializationException extends Exception implements Serializable

Class edu.cmu.tetrad.calculator.expression.VariableExpression

class VariableExpression extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

variable

String variable

The variable that is being evaluated.

Package edu.cmu.tetrad.classify

Class edu.cmu.tetrad.classify.ClassifierBayesUpdaterDiscrete

class ClassifierBayesUpdaterDiscrete extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.)

Parameters:

s - The input stream.

Throws:

IOException - If an IO error occurs.

ClassNotFoundException - If a class is not found.

Serialized Fields

bayesIm

BayesIm bayesIm

The BayesIm instance used to create an updater. Supplied as an argument to the constructor.

bayesImVars

List<Node> bayesImVars

The variables in the dataset to be classified. These should be the same variables as in the training dataset according to the "equals" method of DiscreteVariable.

classifications

int[] classifications

The classifications of the target variable.

marginals

double[][] marginals

The marginals.

numCases

int numCases

The number of cases in the dataset.

percentCorrect

double percentCorrect

The percentage of correct estimates of the target variable. This will be set to a meaningful value upon completion of the crossTabulate method.

targetVariable

DiscreteVariable targetVariable

The target variable (inferred from its name).

testData

DataSet testData

The dataset to be classified.

totalUsableCases

int totalUsableCases

The number of usable cases in the dataset.

Package edu.cmu.tetrad.data

Class edu.cmu.tetrad.data.AbstractVariable

class AbstractVariable extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

name

String name

Name of this variable.

selectionBias

boolean selectionBias

True just in case this node is a selection bias node.

Class edu.cmu.tetrad.data.BoxDataSet

class BoxDataSet extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

caseIds

Map<Integer,String> caseIds

Case ID's. These are strings associated with some or all of the cases of the dataset.

columnToTooltip

Map<String,String> columnToTooltip

The name of the data model. This is not used internally; it is only here in case an external class wants this dataset to have a name.

dataBox

DataBox dataBox

The container storing the data. Rows are cases; columns are variables. The order of columns is coordinated with the order of variables in getVariables().

knowledge

Knowledge knowledge

The knowledge associated with this data.

multipliers

Map<Integer,Integer> multipliers

A map from cases to case multipliers. If a case is not in the domain of this map, its case multiplier is by default 1. This is the number of repetitions of the case in the dataset. The sample size is obtained by summing over these multipliers.

name

String name

The name of the data model. This is not used internally; it is only here in case an external class wants this dataset to have a name.

outputDelimiter

char outputDelimiter

The character used as a delimiter when the dataset is printed.

selection

Set<Node> selection

The set of selected variables.

variables

List<Node> variables

The list of variables. These correspond columnwise to the columns of data.

Class edu.cmu.tetrad.data.ByteDataBox

class ByteDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

byte[][] data

The stored byte data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.ContinuousDiscretizationSpec

class ContinuousDiscretizationSpec extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

breakpoints

double[] breakpoints

Breakpoints, for continuous data.

categories

List<String> categories

Categories, for discrete data.

method

int method

The method used.

Class edu.cmu.tetrad.data.ContinuousVariable

class ContinuousVariable extends AbstractVariable implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

attributes

Map<String,Object> attributes

The node type.

centerX

int centerX

The x coordinate of the center of the node.

centerY

int centerY

The y coordinate of the center of the node.

nodeType

NodeType nodeType

The node type.

nodeVariableType

NodeVariableType nodeVariableType

Node variable type (domain, interventional status, interventional value..) of this node variable

rank

int rank

The rank, or -1 if none is set. If set, just be >= 9,

Class edu.cmu.tetrad.data.CorrelationMatrix

class CorrelationMatrix extends CovarianceMatrix implements Serializable

serialVersionUID:

23L

Class edu.cmu.tetrad.data.CorrelationMatrixOnTheFly

class CorrelationMatrixOnTheFly extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

cov

ICovarianceMatrix cov

The covariance matrix. Cannot be null. Must be symmetric and positive definite.

variables

List<Node> variables

The variables (in order) for this covariance matrix.

verbose

boolean verbose

Whether to print out verbose messages.

Class edu.cmu.tetrad.data.CovarianceMatrix

class CovarianceMatrix extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

_covariancesMatrix

Matrix _covariancesMatrix

The wrapped covariance matrix data.

knowledge

Knowledge knowledge

The knowledge for this data.

name

String name

The name of the covariance matrix.

sampleSize

int sampleSize

The size of the sample from which this covariance matrix was calculated.

selectedVariables

Set<Node> selectedVariables

The list of selected variables.

variables

List<Node> variables

The variables (in order) for this covariance matrix.

Class edu.cmu.tetrad.data.CovarianceMatrixOnTheFly

class CovarianceMatrixOnTheFly extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

knowledge

Knowledge knowledge

The knowledge for this data.

matrix

Matrix matrix

Stored matrix data. Should be square. This may be set by derived classes, but it must always be set to a legitimate covariance matrix.

name

String name

The name of the covariance matrix.

sampleSize

int sampleSize

The size of the sample from which this covariance matrix was calculated.

selectedVariables

Set<Node> selectedVariables

The list of selected variables.

variables

List<Node> variables

The variables (in order) for this covariance matrix.

variances

double[] variances

The variances of the variables.

vectors

double[][] vectors

The vectors for the variables.

verbose

boolean verbose

Whether to print out verbose information.

Class edu.cmu.tetrad.data.DataModelList

class DataModelList extends AbstractList<DataModel> implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

knowledge

Knowledge knowledge

The knowledge for this data.

modelList

List<DataModel> modelList

The list of models.

name

String name

The name of the DataModelList.

selectedModel

DataModel selectedModel

The selected model (may be null).

Class edu.cmu.tetrad.data.DelimiterType

class DelimiterType extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

readResolve

Object readResolve()
            throws ObjectStreamException

readResolve.

Throws:

ObjectStreamException - if any.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

ordinal

int ordinal

The ordinal of this type.

Class edu.cmu.tetrad.data.DiscreteDiscretizationSpec

class DiscreteDiscretizationSpec extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

categories

List<String> categories

Categories, for discrete data.

remap

int[] remap

Discrete remapping of categories, for discrete data.

Class edu.cmu.tetrad.data.DiscreteVariable

class DiscreteVariable extends AbstractVariable implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

accommodateNewCategories

boolean accommodateNewCategories

True iff new variables should be allowed to be constructed to replace this one, accommodating new categories.

attributes

Map<String,Object> attributes

Attributes of the node.

categoriesCopy

List<String> categoriesCopy

A copy of the category list is stored here for when the discrete variable is deserialized. On deserialization, STORED_CATEGORY_LISTS will be constructed if it hasn't been already, and this list will be looked up on the "bulletin board" to see if a permutation of it already exists.

categoryNamesDisplayed

boolean categoryNamesDisplayed

True iff the category categories for this variable should be displayed; false if the integer indices of categories should be displayed.

centerX

int centerX

The x coordinate of the center of the node.

centerY

int centerY

The y coordinate of the center of the node.

discreteVariableType

DiscreteVariableType discreteVariableType

The discreteVariableType of discrete variable this is.

nodeType

NodeType nodeType

The node discreteVariableType.

nodeVariableType

NodeVariableType nodeVariableType

Node variable type (domain, interventional status, interventional value, ...) of this node variable

Class edu.cmu.tetrad.data.DiscreteVariableType

class DiscreteVariableType extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

readResolve

Object readResolve()
            throws ObjectStreamException

Returns the ordinal of this type.

Throws:

ObjectStreamException - if any.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

ordinal

int ordinal

The ordinal of this type.

Class edu.cmu.tetrad.data.DoubleDataBox

class DoubleDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

double[][] data

The stored double data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.FloatDataBox

class FloatDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

float[][] data

The stored float data.

Class edu.cmu.tetrad.data.IndependenceFacts

class IndependenceFacts extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

knowledge

Knowledge knowledge

The knowledge.

name

String name

The name of the independence facts.

nodes

List<Node> nodes

The nodes in the graph.

unsortedFacts

Set<IndependenceFact> unsortedFacts

The unsorted facts.

Class edu.cmu.tetrad.data.IntDataBox

class IntDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

int[][] data

The stored short data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.Knowledge

class Knowledge extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Migrates serialized objects from before knowledge groups were enforced directly: the pairwise rules that mirrored each group are removed from the forbidden and required rule lists, so that the groups (still present, and now consulted directly) are not double-counted and editing or removing a group behaves as it does for newly built objects. This matches the old removeKnowledgeGroup, which removed the mirrored rule on removal. Also ensures every group has a cached extent.

Parameters:

in - the stream to read from.

Throws:

IOException - if the stream cannot be read.

ClassNotFoundException - if a class in the stream cannot be found.

Serialized Fields

defaultToKnowledgeLayout

boolean defaultToKnowledgeLayout

The default to knowledge layout.

forbiddenRulesSpecs

List<OrderedPair<Set<String>>> forbiddenRulesSpecs

This needs to be a list for backward compatibility. Need to check when adding a new spec whether it's already in the list.

knowledgeGroupRules

Map<KnowledgeGroup, OrderedPair<Set<String>>> knowledgeGroupRules

The resolved extents of the knowledge groups: for each group, the pair of variable sets its from- and to-specs matched when the group was added or last set. Wildcards are resolved against the variables known at that time.

knowledgeGroups

List<KnowledgeGroup> knowledgeGroups

The knowledge groups. These are enforced directly, as groups, by Knowledge.isForbidden(String, String) and Knowledge.isRequired(String, String) (through Knowledge.isForbiddenByGroups(String, String) and Knowledge.isRequiredByGroups(String, String)); they are not compiled into Knowledge.forbiddenRulesSpecs or Knowledge.requiredRulesSpecs. (Formerly they were mirrored into those lists, which made removing a group delete any identical explicitly set rule; Knowledge.readObject(ObjectInputStream) migrates old serialized objects.)

requiredRulesSpecs

List<OrderedPair<Set<String>>> requiredRulesSpecs

This needs to be a list for backward compatibility. Need to check when adding a new spec whether it's already in the list.

testingData

DataSet testingData

Represents an ancillary dataset associated with this knowledge object, which can be used, e.g., for testing purposes. Can be null.

tierSpecs

List<Set<String>> tierSpecs

The tier specs.

tierStructures

List<KnowledgeTierStructure> tierStructures

Additional, named tier structures, independent of the main tiers and of one another; see KnowledgeTierStructure. May be null in objects serialized before this field existed; always accessed through Knowledge.tierStructures().

variables

Set<String> variables

The variable names.

Class edu.cmu.tetrad.data.KnowledgeEdge

class KnowledgeEdge extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

from

String from

The tail node of the edge.

to

String to

The head node of the edge.

Class edu.cmu.tetrad.data.KnowledgeGroup

class KnowledgeGroup extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

fromGroup

Set<String> fromGroup

The left group of variables.

toGroup

Set<String> toGroup

The right group of variables.

type

int type

The type of group that this is (currently either required or forbidden).

Class edu.cmu.tetrad.data.KnowledgeTierStructure

class KnowledgeTierStructure extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

forbiddenWithin

List<Boolean> forbiddenWithin

For each tier, whether edges within that tier are forbidden. Kept parallel to KnowledgeTierStructure.tiers.

name

String name

The display name of this structure -- e.g., "Exams". May contain spaces.

tiers

List<Set<String>> tiers

The tiers, lowest first. Insertion order of names is kept for stable rendering.

Class edu.cmu.tetrad.data.LongDataBox

class LongDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

long[][] data

The stored long data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.MixedDataBox

class MixedDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

continuousData

double[][] continuousData

The continuous data.

discreteData

int[][] discreteData

The discrete data.

numRows

int numRows

The number of rows in the dataset.

variables

List<Node> variables

The variables in the dataset.

Class edu.cmu.tetrad.data.NumberObjectDataSet

class NumberObjectDataSet extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

columnToTooltip

Map<String,String> columnToTooltip

The map from column names to tooltips.

data

Number[][] data

The container storing the data. Rows are cases; columns are variables. The order of columns is coordinated with the order of variables in getVariable().

knowledge

Knowledge knowledge

The knowledge associated with this data.

name

String name

The name of the data model. This is not used internally; it is only here in case an external class wants this dataset to have a name.

outputDelimiter

char outputDelimiter

The character used as a delimiter when the dataset is printed.

selection

Set<Node> selection

The set of selected variables.

variables

List<Node> variables

The list of variables. These correspond columnwise to the columns of data.

Class edu.cmu.tetrad.data.ShortDataBox

class ShortDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

short[][] data

The stored short data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.SplitCasesSpec

class SplitCasesSpec extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

breakpoints

int[] breakpoints

Breakpoints, for continuous data.

sampleSize

int sampleSize

Sample size.

splitNames

List<String> splitNames

Split names.

Class edu.cmu.tetrad.data.TimeSeriesData

class TimeSeriesData extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

data2

Matrix data2

The data.

knowledge

Knowledge knowledge

The knowledge about the data.

name

String name

The name of the data.

varNames

List<String> varNames

The names of the variables.

Class edu.cmu.tetrad.data.UnmixSpec

class UnmixSpec extends Object implements Serializable

serialVersionUID:

-7113246204343961993L

Serialized Fields

annealStartT

double annealStartT

Represents the starting temperature for annealing in a process. This parameter controls the initial temperature for annealing. The default value is set to 0.8.

annealSteps

int annealSteps

Represents the number of steps for annealing in a process. This parameter controls the number of iterations for annealing. The default value is set to 15 steps.

autoSelectK

boolean autoSelectK

A flag that determines whether the value of 'k' in an operation or calculation should be automatically selected by the system. When set to true, the system determines the appropriate value of 'k' without user intervention. If false, the value of 'k' must be provided explicitly by the user or another part of the program.

bossPenaltyDiscount

double bossPenaltyDiscount

Represents the discount rate applied as a penalty imposed by the "boss". This value is used to calculate or adjust certain conditions or fees associated with tasks or operations where the penalty is relevant. The default value is 2.0.

covarianceMode

UnmixSpec.CovarianceMode covarianceMode

The covariance mode setting used to determine how covariance is calculated in specific operations or algorithms. This variable is an instance of the UnmixSpec.CovarianceMode enumeration and dictates the strategy for covariance estimation.

The available modes in UnmixSpec.CovarianceMode may include: - AUTO: Automatically selects the appropriate covariance handling method based on context. - Other specific modes depending on the UnmixSpec.CovarianceMode implementation.

This variable plays an essential role in configuring processes or computations that rely on covariance-related functionality or optimization.

emMaxIters

int emMaxIters

Defines the maximum number of iterations allowed for the Expectation-Maximization (EM) algorithm to converge. This value is used to limit the computational effort when training or optimizing models using the EM approach.

The default value is set to 300 iterations.

fullSigmaSafetyMargin

int fullSigmaSafetyMargin

Used only when AUTO: require n/K >= p + safetyMargin to use FULL

graphLearner

UnmixSpec.GraphLearner graphLearner

A private instance variable representing the graph learning strategy. `graphLearner` is set to the `GraphLearner.BOSS` as the default learning method. The value determines the algorithm or approach used in the learning process within the graph-based operations.

K

int K

Represents an integer constant used within the class. The variable is initialized with a default value of 2. This value may signify a specific configuration or a predefined parameter relevant to the class operations.

Kmax

int Kmax

The maximum allowable value for a certain parameter or configuration in the application. This variable is used to define a constant limit for operations or calculations. It is initialized to a default value of 4.

kmeansRestarts

int kmeansRestarts

Represents the number of times the k-means clustering algorithm will be restarted with different initial centroids to improve the chances of finding a global optimum.

This value determines the number of random initializations performed during the k-means clustering process. A higher value increases the likelihood of achieving better clustering results at the expense of additional computation time.

Kmin

int Kmin

Represents the minimum value of K being used in the context of the program. This variable is initialized to 1 and is typically utilized to define a lower boundary or threshold for calculations or iterations involving K.

logIntermediate

boolean logIntermediate

Determines if intermediate logging is enabled.

pcAlpha

double pcAlpha

Represents the alpha value for a specific probability or calculation context. This variable is often used to adjust sensitivity or weighting in algorithms. In this case, it is initialized with a default value of 0.01.

pcColliderStyle

UnmixSpec.ColliderStyle pcColliderStyle

Represents the collision style for player-controlled objects in the application. The variable is initialized to the maximum precision collision style, defined as ColliderStyle.MAX_P. Determines how collisions are handled or processed for player-controlled entities. Can be modified to adjust the collision handling strategy during runtime.

randomSeed

long randomSeed

Represents the random seed for generating random numbers. This parameter controls the initial seed for random number generation. The default value is set to 13.

ridge

double ridge

Represents the ridge regularization parameter used in machine learning algorithms such as Ridge Regression. This parameter helps prevent overfitting by penalizing large coefficients. A smaller value indicates less regularization, whereas a larger value increases the regularization strength.

robustScaleResiduals

boolean robustScaleResiduals

A flag that determines whether residuals should be scaled robustly. When set to true, residual scaling is performed in a manner that is less sensitive to outliers, improving the robustness of the scaling process. If set to false, residuals are not scaled robustly.

saveDiagnostics

boolean saveDiagnostics

Determines if diagnostic information should be saved during the process.

shrinkage

double shrinkage

Represents the shrinkage regularization parameter used in machine learning algorithms such as Elastic Net. This parameter helps prevent overfitting by penalizing large coefficients. A smaller value indicates less regularization, whereas a larger value increases the regularization strength.

supersetScore

UnmixSpec.SupersetScore supersetScore

Represents the score type used for evaluating the similarity or ranking between elements in a superset. Defaults to SupersetScore.KENDALL. The value of this variable determines the method of computation for scoring or comparison within superset-related contexts.

supersetTopM

int supersetTopM

The maximum number of elements to be included in the superset. This defines the top limit for the collection or processing within a superset-related operation.

useParentSuperset

boolean useParentSuperset

A flag indicating whether to use the parent superset in some operable context. When set to true, the logic will incorporate or rely on the parent superset instead of solely focusing on the current or individual scope. Otherwise, it will bypass or exclude the parent superset in the operation.

Class edu.cmu.tetrad.data.VerticalDoubleDataBox

class VerticalDoubleDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

double[][] data

The stored double data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Class edu.cmu.tetrad.data.VerticalIntDataBox

class VerticalIntDataBox extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

data

int[][] data

The stored int data.

numCols

int numCols

The number of columns (tracked because it may be zero).

numRows

int numRows

The number of rows (tracked because it may be zero).

Package edu.cmu.tetrad.data.missing

Class edu.cmu.tetrad.data.missing.MissingDataSpec

class MissingDataSpec extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

emMaxIterations

int emMaxIterations

Maximum number of EM iterations. Used by EM_COVARIANCE.

emRidge

double emRidge

Ridge added to the diagonal in the EM M-step, for numerical stability. Used by EM_COVARIANCE.

emTolerance

double emTolerance

Convergence tolerance for the EM observed-data log likelihood. Used by EM_COVARIANCE.

essMode

MissingDataSpec.EffectiveSampleSizeMode essMode

How the effective sample size for penalized scores is determined when the analysis is run on an estimated covariance matrix.

numImputations

int numImputations

The number of imputed datasets, m. Used by MULTIPLE_IMPUTATION.

policy

MissingDataPolicy policy

The policy.

seed

long seed

Random seed for stochastic policies (multiple imputation); -1 means no fixed seed.

Package edu.cmu.tetrad.data.simulation

Class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndGraphs

class LoadContinuousDataAndGraphs extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graphs

List<Graph> graphs

The graphs.

path

String path

The path.

usedParameters

List<String> usedParameters

The used parameters.

Class edu.cmu.tetrad.data.simulation.LoadContinuousDataAndSingleGraph

class LoadContinuousDataAndSingleGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graph

Graph graph

The graph.

parametersValues

Parameters parametersValues

The parameters values.

path

String path

The path.

usedParameters

List<String> usedParameters

The used parameters.

Class edu.cmu.tetrad.data.simulation.LoadContinuousDataSmithSim

class LoadContinuousDataSmithSim extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

graph

Graph graph

The graph.

parametersValues

Parameters parametersValues

The parameters values.

path

String path

The path.

usedParameters

List<String> usedParameters

The used parameters.

Class edu.cmu.tetrad.data.simulation.LoadDataAndGraphs

class LoadDataAndGraphs extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSets

List<DataSet> dataSets

The data sets.

description

String description

The description.

graphs

List<Graph> graphs

The graphs.

path

String path

The path.

usedParameters

List<String> usedParameters

The used parameters.

Class edu.cmu.tetrad.data.simulation.LoadDataFromFileWithoutGraph

class LoadDataFromFileWithoutGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

dataSet

DataSet dataSet

The data set.

parameterValues

Map<String,Object> parameterValues

The parameter values.

path

String path

The path.

Package edu.cmu.tetrad.estimate.v1

Class edu.cmu.tetrad.estimate.v1.AdjustmentEffectEstimatorV1.ConfigV1

class ConfigV1 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

basisDegree

int basisDegree

Represents the basis degree for continuous covariates in the configuration. This value determines the degree of the basis functions to be utilized, typically used in regression models to capture polynomial relationships in the data. By default, it is set to 3, which corresponds to a cubic polynomial basis.

bootstrapB

int bootstrapB

Number of bootstrap

ciAlpha

double ciAlpha

Confidence level for constructing confidence intervals. A value of 0.05 corresponds to a 95% confidence interval.

includeTreatmentInteractions

boolean includeTreatmentInteractions

Indicates whether treatment interactions (e.g., X * φ(Z)) should be included in the outcome regression model. When set to true, the model incorporates interactions between treatment variables and covariate functions, which may improve predictive accuracy in outcome modeling.

irlsTol

double irlsTol

Tolerance for convergence in IRLS algorithm. Smaller values result in more iterations for convergence.

maxIrlsIter

int maxIrlsIter

Maximum number of

propensityClipEps

double propensityClipEps

Propensity clipping epsilon for handling extreme propensity scores. A small positive value helps prevent extreme values from dominating the model.

ridge

double ridge

Ridge stabilization parameter for OLS and IRLS algorithms. A small positive value helps stabilize the solution by adding a regularization term to the objective function. Set to 0 to disable.

winsorFrac

double winsorFrac

Fraction of data to winsorize for min/max scaling to [-1,1]. Set to 0 to disable winsorization.

Class edu.cmu.tetrad.estimate.v1.AdjustmentEffectEstimatorV1.EffectEstimateResultV1

class EffectEstimateResultV1 extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

adjustmentSet

List<String> adjustmentSet

A list of variable names that are included in the adjustment set. The adjustment set is typically used in causal inference to control for confounding variables. It contains the variables that are conditioned on to estimate the effect of an exposure on an outcome.

ateDr

double ateDr

Represents the average treatment effect on the outcome (ATE) estimated using the doubly robust (DR) method. This value quantifies the expected change in the outcome resulting from a unit change in the treatment variable while simultaneously leveraging outcome regression (OR) and propensity score models to account for confounding factors. The DR approach ensures robustness against misspecification of either the outcome or propensity score models.

ateOr

double ateOr

Represents the average treatment effect on the outcome (ATE) estimated using the outcome regression (OR) method. This value quantifies the expected change in the outcome resulting from a unit change in the treatment variable while controlling for confounding factors.

ciHiDr

double ciHiDr

Represents the lower bound of the confidence interval for the DR effect size (DR) in the context of effect estimation. This value provides a measure of uncertainty around the estimated DR effect size, indicating the lowest plausible value of the DR within a specified confidence level (e.g., 95%).

ciHiOr

double ciHiOr

Represents the lower bound of the confidence interval for the odds ratio (OR) in the context of effect estimation. This value provides a measure of uncertainty around the estimated odds ratio, indicating the lowest plausible value of the OR within a specified confidence level (e.g., 95%).

ciLoDr

double ciLoDr

Represents the lower bound of the confidence interval for the DR effect size (DR) in the context of effect estimation. This value provides a measure of uncertainty around the estimated DR effect size, indicating the lowest plausible value of the DR within a specified confidence level (e.g., 95%).

ciLoOr

double ciLoOr

Represents the lower bound of the confidence interval for the odds ratio (OR) in the context of effect estimation. This value provides a measure of uncertainty around the estimated odds ratio, indicating the lowest plausible value of the OR within a specified confidence level (e.g., 95%).

fracClipped

double fracClipped

Represents the fraction of observations that were clipped during the effect estimation process. Clipping occurs when extreme values are removed to prevent skewing the results.

maxProp

double maxProp

Represents the minimum proportion of observations used in the effect estimate calculation. This value is determined during the analysis process and provides information about the smallest proportion of the data that contributed to the result.

minProp

double minProp

Represents the minimum proportion of observations used in the effect estimate calculation. This value is determined during the analysis process and provides information about the smallest proportion of the data that contributed to the result.

n

int n

The sample size used in the effect estimation process. This field represents the number of data points or observations considered during the calculation of the effect estimate results.

seDrBoot

double seDrBoot

The standard error of the Doubly Robust (DR) estimation for the effect size, computed using bootstrap resampling. This metric provides a measure of variability or uncertainty associated with the DR effect size estimate obtained through bootstrapping.

seOrBoot

double seOrBoot

Represents the bootstrap standard error of the average treatment effect (ATE) estimated using the outcome regression (OR) method. This value provides a measure of variability or uncertainty associated with the ATE estimate derived from the OR approach. It is calculated using a bootstrap resampling technique, which involves repeatedly sampling the dataset with replacement and recalculating the ATE to assess the stability of the estimate.

Package edu.cmu.tetrad.graph

Class edu.cmu.tetrad.graph.Dag

class Dag extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.)

Parameters:

s - The object input stream.

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The set of ambiguous triples.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The set of dotted underline triples.

graph

Graph graph

The graph.

underLineTriples

Set<Triple> underLineTriples

The set of underline triples.

Class edu.cmu.tetrad.graph.Edge

class Edge extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bold

boolean bold

Whether the edge is bold.

edgeTypeProbabilities

List<EdgeTypeProbability> edgeTypeProbabilities

The edge type probabilities.

endpoint1

Endpoint endpoint1

The endpoint at the first node.

endpoint2

Endpoint endpoint2

The endpoint at the second node.

highlighted

boolean highlighted

Whether the edge is highlighted.

node1

Node node1

The first node.

node2

Node node2

The second node.

probability

double probability

The probability.

properties

List<Edge.Property> properties

The properties.

Class edu.cmu.tetrad.graph.EdgeListGraph

class EdgeListGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.)

Parameters:

s - a ObjectInputStream object

Throws:

IOException - if any.

ClassNotFoundException - if any.

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The ambiguous triples.

ancestorCache

Map<org.apache.commons.lang3.tuple.Pair<Node,Node>, Boolean> ancestorCache

The cache for the ancestor relationships

ancillaryGraphs

Map<String,Graph> ancillaryGraphs

A map from names of graphs to ancillary graphs for this graph.

attributes

Map<String,Object> attributes

The attributes.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The dotted underline triples.

edgeLists

Map<Node, Set<Edge>> edgeLists

Map from each node to the List of edges connected to that node.

edgesSet

Set<Edge> edgesSet

The edges in the graph.

namesHash

Map<String,Node> namesHash

A hash from node names to nodes;

nodes

List<Node> nodes

A list of the nodes in the graph, in the order in which they were added.

potentiallyDirectedPathCache

Map<org.apache.commons.lang3.tuple.Pair<Node,Node>, Boolean> potentiallyDirectedPathCache

The cache for the potentially directed path relationships

underLineTriples

Set<Triple> underLineTriples

The underline triples.

Class edu.cmu.tetrad.graph.EdgeTypeProbability

class EdgeTypeProbability extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

edgeType

EdgeTypeProbability.EdgeType edgeType

The edge type.

probability

double probability

The probability.

properties

List<Edge.Property> properties

The properties.

Class edu.cmu.tetrad.graph.GraphNode

class GraphNode extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - The input stream.

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

attributes

Map<String,Object> attributes

The attributes of the node.

centerX

int centerX

The x coordinate of the center of the node.

centerY

int centerY

The y coordinate of the center of the node.

name

String name

The name of the node.

nodeType

NodeType nodeType

The type of the node.

See Also:

• NodeType

nodeVariableType

NodeVariableType nodeVariableType

Node variable type (domain, interventional status, interventional value..) of this node variable

selectionBias

boolean selectionBias

Whether the node is selected as a bias node.

Class edu.cmu.tetrad.graph.IndependenceFact

class IndependenceFact extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

_z

Set<Node> _z

The conditioning set.

x

Node x

The first node conditioned nodes.

y

Node y

The second conditioned node.

Class edu.cmu.tetrad.graph.LagGraph

class LagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The set of ambiguous triples.

attributes

Map<String,Object> attributes

The map from variables to their attributes.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The set of dotted underline triples.

graph

Dag graph

The graph.

laggedVariables

Map<String, List<Node>> laggedVariables

The map from variables to their lagged variables.

paths

Paths paths

The paths

underLineTriples

Set<Triple> underLineTriples

The set of underline triples.

variables

List<String> variables

The list of variables in the getModel time lag.

Class edu.cmu.tetrad.graph.LagReplicationPolicy

class LagReplicationPolicy extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

maxLag

Integer maxLag

The maximum allowable lag in the replication policy. This variable defines the upper boundary for lag values permitted by the LagReplicationPolicy. It is immutable and is set during the initialization of the object.

minLag

Integer minLag

Represents the minimum allowable lag value for the lag-based replication policy in the LagReplicationPolicy class.

This field defines the lowest lag threshold that will be utilized during the evaluation and processing of edges in graph data. It ensures that replication policies are applied with a lag no less than this specified value.

The value of minLag is immutable and must be provided at the time of construction of the LagReplicationPolicy instance.

step

int step

Optional: stride for seasonal mirroring (e.g., step=12 for monthly-to-yearly).

Class edu.cmu.tetrad.graph.OrderedPair

class OrderedPair extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

first

E first

The "First" node.

second

E second

The "second" node.

Class edu.cmu.tetrad.graph.Paths

class Paths extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

graph

Graph graph

The graph.

Class edu.cmu.tetrad.graph.ReplicatingGraph

class ReplicatingGraph extends EdgeListGraph implements Serializable

Serialized Fields

policy

EdgeReplicationPolicy policy

The edge replication policy used for determining which edges should be mirrored and kept in sync in the graph. This policy defines the behavior for ensuring consistency across related edges, enabling algorithms to handle replication and updates in a uniform and predictable manner. The specified policy must adhere to rules of the EdgeReplicationPolicy interface and is applied during operations that modify edges in the graph.

Class edu.cmu.tetrad.graph.SemGraph

class SemGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.)

Parameters:

s - The object input stream.

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The ambiguous triples.

attributes

Map<String,Object> attributes

The attributes of the graph.

cpdag

boolean cpdag

True if the graph is a CPDAG.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The dotted underlines.

errorNodes

Map<Node,Node> errorNodes

A map from nodes to their error nodes, if they exist. This includes variables nodes to their error nodes and error nodes to themselves. Added because looking them up in the graph was not scalable.

graph

Graph graph

The underlying graph that stores all the information. This needs to be an EdgeListGraph or something at least that can allow nodes to quickly be added or removed.

pag

boolean pag

True if the graph is a PAG.

paths

Paths paths

The paths of the graph.

showErrorTerms

boolean showErrorTerms

True if error terms for exogenous terms should be shown.

underLineTriples

Set<Triple> underLineTriples

The underlines.

Class edu.cmu.tetrad.graph.TimeLagGraph

class TimeLagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The set of ambiguous triples.

attributes

Map<String,Object> attributes

A node in a time lag graph.

cpdag

boolean cpdag

Whether the graph is a CPDAG.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The set of dotted underlined triples.

graph

EdgeListGraph graph

A node in a time lag graph.

lag0Nodes

List<Node> lag0Nodes

The nodes in lag 0.

maxLag

int maxLag

The maximum lag.

numInitialLags

int numInitialLags

The number of initial lags.

pag

boolean pag

Whether the graph is a PAG.

paths

Paths paths

The paths in the graph.

underLineTriples

Set<Triple> underLineTriples

The set of underlined triples.

Class edu.cmu.tetrad.graph.Triple

class Triple extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

x

Node x

The first node in the triple.

y

Node y

The second node in the triple.

z

Node z

The third node in the triple.

Class edu.cmu.tetrad.graph.Underlines

class Underlines extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

ambiguousTriples

Set<Triple> ambiguousTriples

The ambiguous triples.

dottedUnderLineTriples

Set<Triple> dottedUnderLineTriples

The dotted underlines.

graph

Graph graph

The graph.

underLineTriples

Set<Triple> underLineTriples

The underlines.

Package edu.cmu.tetrad.hybridcg

Class edu.cmu.tetrad.hybridcg.HybridCgModel.HybridCgIm

class HybridCgIm extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

contParams

double[][][] contParams

Continuous child: for node y, params[y] is rows x (m+2) where m = #cont parents; cols = [Mean, coeffs..., variance]

discProbs

double[][][] discProbs

Discrete child: probs[y] is rows x card(y)

pm

HybridCgModel.HybridCgPm pm

A probabilistic model used for hybrid causal graph inference. This field represents an instance of HybridCgModel.HybridCgPm, providing the necessary structure and parameters to define the hybrid causal graph model.

The pm is immutable, ensuring the consistency and integrity of the model throughout its usage in the associated HybridCgModel.HybridCgIm instance.

Typical operations leveraging this field include accessing the model’s parameters, retrieving conditional probabilities, and determining node dependencies within the causal graph.

This field encapsulates all the key information required to perform probabilistic reasoning and to simulate observations for both discrete and continuous variables in the hybrid causal structure.

rowCaseCounts

int[][] rowCaseCounts

Number of complete cases behind each local-table row, indexed [node][row]. A value of -1 means the count is unknown, which is the case for any IM that was built by hand rather than estimated from data. Estimation fills this in for every node and row, including rows with a count of zero.

Class edu.cmu.tetrad.hybridcg.HybridCgModel.HybridCgPm

class HybridCgPm extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

categories

List<String>[] categories

Represents the categories associated with each node in the hybrid causal probabilistic model. This array defines the categorical values for discrete nodes and remains null for continuous nodes.

For a discrete node, the list size corresponds to the node's cardinality (number of categories), and each entry in the list denotes a specific category label. If a node is continuous,

contParentCutpointsForDiscreteChild

double[][][] contParentCutpointsForDiscreteChild

For DISCRETE children ONLY: if a continuous parent exists, we discretize it. Store per (child, contParentIndexInOrder) the monotonically increasing cutpoints. bins = cutpoints.length + 1

contParents

int[][] contParents

Parent lists split by type, pointing to indices into nodes[]

dag

Graph dag

Represents a structural model for hybrid Bayesian networks, which may include both discrete and continuous variables.

discParents

int[][] discParents

Parent lists split by type, pointing to indices into nodes[]

isDiscrete

boolean[] isDiscrete

Variable typing and categories (for discrete variables only)

nodes

Node[] nodes

An array representing the nodes in the hybrid causal graph probabilistic model. Each element corresponds to a specific node in the directed acyclic graph (DAG), reflecting the structure and dependencies of the model.

This field is initialized during the construction of the model and contains the ordered representation of nodes used throughout various computations and methods within the model.

The nodes can be either discrete or continuous, as defined by the model's configuration.

Class edu.cmu.tetrad.hybridcg.HybridCgPruneReport

class HybridCgPruneReport extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

alpha

double alpha

The significance level the elimination used.

deletions

List<HybridCgPruneReport.Deletion> deletions

The list of edges that were deleted.

prunedGraph

Graph prunedGraph

The pruned graph.

shareVariance

boolean shareVariance

Indicates whether continuous-child fits shared a single residual variance across strata in the context of graph pruning and statistical testing. This value is determined during the construction of a Prune Report and reflects if the shared variance assumption was used when fitting continuous child variables in the model.

untested

List<String> untested

The list of edges that were not tested.

Class edu.cmu.tetrad.hybridcg.HybridCgPruneReport.Deletion

class Deletion extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

childName

String childName

Name of the child variable (head of the deleted edge).

df

int df

The sparse-adjusted degrees of freedom at the time of removal.

n

int n

The available-case count of the family the test was run on.

parentName

String parentName

Name of the parent variable (tail of the deleted edge).

pValue

double pValue

The LRT p-value at the time of removal.

statistic

double statistic

The LRT statistic at the time of removal.

step

int step

Elimination round within this child at which the edge fell (0-based).

Package edu.cmu.tetrad.regression

Class edu.cmu.tetrad.regression.LogisticRegression

class LogisticRegression extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - a ObjectInputStream object

Throws:

IOException - if an error occurs

ClassNotFoundException - if an error occurs

Serialized Fields

alpha

double alpha

The default alpha level which may be specified otherwise in the GUI

dataCols

double[][] dataCols

The data converted into column major, to avoid unnecessary copying.

dataSet

DataSet dataSet

The data set that was supplied.

rows

int[] rows

The rows in the data used for regression.

Class edu.cmu.tetrad.regression.LogisticRegression.Result

class Result extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The alpha level.

chiSq

double chiSq

The chi square statistic.

coefs

double[] coefs

The array of regression coefficients.

intercept

double intercept

The intercept.

logLikelihood

double logLikelihood

The log likelihood of the regression.

numRegressors

int numRegressors

The number of regressors.

ny0

int ny0

The number of cases with target = 0.

ny1

int ny1

The number of cases with target = 1.

probs

double[] probs

The array of coefP-values for the regression coefficients.

regressorNames

List<String> regressorNames

The names of the regressors.

stdErrs

double[] stdErrs

The array of standard errors for the regression coefficients.

target

String target

The target.

xMeans

double[] xMeans

The array of means.

xStdDevs

double[] xStdDevs

The array of standard devs.

Class edu.cmu.tetrad.regression.RegressionResult

class RegressionResult extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

alpha

double alpha

Alpha value to determine significance.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

b

double[] b

The array of regression coefficients.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

n

int n

The number of data points.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

p

double[] p

The array of p-values for the regression coefficients.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

r2

double r2

R square value.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

regressorNames

String[] regressorNames

Regressor names.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

res

Vector res

The residuals.

rss

double rss

Residual sums of squares.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

se

double[] se

Standard errors of the coefficients

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

t

double[] t

The array of t-statistics for the regression coefficients.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

zeroInterceptAssumed

boolean zeroInterceptAssumed

True iff this model assumes a zero intercept.

See Also:

• RegressionResult(boolean, String[], int, double[], double[], double[], double[], double, double, double, Vector)

Package edu.cmu.tetrad.search

Class edu.cmu.tetrad.search.Cstar.Record

class Record extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

causeNode

Node causeNode

The cause node.

effect

double effect

The minimum effect size of the predictor on the target across subsamples calculated by IDA.

numCauses

int numCauses

The number of possible causes of the target.

numEffects

int numEffects

The number of possible effects of the target.

pi

double pi

The percentage of the time the predictor is a cause of the target across subsamples.

target

Node target

The effect node.

Class edu.cmu.tetrad.search.NtadExplorer.NtadResult

class NtadResult extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blockA

List<Node> blockA

A list representing the nodes in Block A associated with an NTAD analysis result. Block A is one of the two groups of nodes analyzed during the Nonparametric Test for Associations in Data (NTAD) process, and this field contains the nodes that belong to the first group. This field is initialized during the creation of an instance of the NtadResult class and remains immutable throughout the lifecycle of the object.

blockB

List<Node> blockB

Represents the list of nodes in Block B associated with the NTAD (Network-Theoretic Analysis of Dependence) analysis. Block B corresponds to one of the two substructures examined in the analysis, where each node contributes to the statistical and structural properties being evaluated.

blockSize

int blockSize

Represents the size of the block structures involved in the NTAD analysis.

pValue

double pValue

Represents the p-value from the statistical test associated with the analysis.

rank

int rank

Represents the rank of the canonical correlation analysis (CCA) result.

Package edu.cmu.tetrad.search.blocks

Class edu.cmu.tetrad.search.blocks.BlockSpec

class BlockSpec extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

blocks

List<List<Integer>> blocks

Represents a list of blocks where each block is represented as a list of integers. Each inner list corresponds to a block and contains a series of integer values defining the elements of that block. This field is immutable, ensuring that once it is initialized, its content cannot be modified.

blockVariables

List<Node> blockVariables

Represents a list of Node objects that correspond to the block variables defined in a BlockSpec instance. Each Node in this list is associated with a specific block, and the size of this list must match the size of the blocks list in the corresponding BlockSpec.

This field is immutable and initialized during the construction of the BlockSpec instance.

It provides a way to define and access the variables that are relevant to each block within the block specification.

dataSet

DataSet dataSet

Represents the data set associated with the block specification. This field is immutable and initialized during the construction of a BlockSpec instance. It serves as the core data associated with block operations and validations.

The dataSet field cannot be null and remains constant throughout the lifecycle of the BlockSpec object. It is integral to the functionality of the class, providing necessary contextual or operational data for blocks, block variables, and ranks within the instance.

ranks

List<Integer> ranks

Represents a list of ranks associated with the blocks in the BlockSpec instance. Each rank corresponds to a block and denotes its designated or functional order in the context of the block specification.

The size of this list is expected to match the sizes of other block-specification-related lists such as blocks and block variables to ensure consistency. All rank values are guaranteed to be integers greater than or equal to 1.

This field is immutable and initialized by the constructor during the instantiation of a BlockSpec object.

Package edu.cmu.tetrad.search.score

Class edu.cmu.tetrad.search.score.ScoredGraph

class ScoredGraph extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

graph

Graph graph

The graph.

score

Double score

The score.

Package edu.cmu.tetrad.search.test

Class edu.cmu.tetrad.search.test.CachedIndependenceQueries

class CachedIndependenceQueries extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

cacheHits

LongAdder cacheHits

Counts cache hits and misses so callers can see how many *distinct* queries actually reached the underlying test versus were served from cache. distinctQueries == misses == size of evalCache at steady state.

cacheMisses

LongAdder cacheMisses

Counts cache misses so callers can see how many *distinct* queries actually reached the underlying test versus were served from cache. distinctQueries == misses == size of evalCache at steady state.

errorPolicy

CachedIndependenceQueries.ErrorPolicy errorPolicy

Represents the error handling strategy employed when evaluating an independence query in the context of cached independence tests. The variable determines how the system should react to errors or exceptions encountered during the evaluation process.

Possible values: - ErrorPolicy.TREAT_AS_INDEPENDENT: Treats an error as if the variables are independent. - ErrorPolicy.TREAT_AS_DEPENDENT: Treats an error as if the variables are dependent. - ErrorPolicy.RETHROW: Propagates the error by rethrowing the encountered exception.

This variable is declared as volatile to ensure thread-safe visibility of its updates across multiple threads.

evalCache

ConcurrentMap<edu.cmu.tetrad.search.test.CachedIndependenceQueries.QueryKey, CachedIndependenceQueries.Eval> evalCache

Cache keyed by structured QueryKey.

Record Class edu.cmu.tetrad.search.test.CachedIndependenceQueries.Eval

class Eval extends Record implements Serializable

serialVersionUID:

23L

Serialized Fields

independent

boolean independent

The field for the independent record component.

pValue

double pValue

The field for the pValue record component.

Class edu.cmu.tetrad.search.test.IndependenceResult

class IndependenceResult extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

fact

IndependenceFact fact

The fact itself.

indep

boolean indep

The conditional independence result, true if the fact holds, false if not.

isValid

boolean isValid

Whether the result is valid or not. A test is not valid if the test is not able to determine whether the fact holds or not.

pValue

double pValue

The p-values of the independence result, under the null (independence) hypothesis.

score

double score

The score of the test, which is alpha - p if the test returns a p-value or else a bump if the test is based on a score.

Package edu.cmu.tetrad.search.utils

Class edu.cmu.tetrad.search.utils.AlmostCycleRemover

class AlmostCycleRemover extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

B

Map<Node, Set<Edge>> B

A map of nodes to bidirected edges for them.

M

Map<Node, Set<Node>> M

A map of nodes to parents oriented by triples for them.

T

Map<Node, Set<Triple>> T

A map of nodes to triples for them.

Class edu.cmu.tetrad.search.utils.SepsetMap

class SepsetMap extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help).

Parameters:

s - a ObjectInputStream object

Throws:

IOException - if an error occurs

ClassNotFoundException - if an error occurs

Serialized Fields

parents

Map<Node, HashSet<Node>> parents

The map from pairs of nodes to separating sets.

pValues

Map<Set<Node>, Double> pValues

The map from pairs of nodes to p-values.

sepsets

Map<Set<Node>, Set<Node>> sepsets

The map from pairs of nodes to separating sets.

Class edu.cmu.tetrad.search.utils.Sextad

class Sextad extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

i

int i

The first node.

j

int j

The second node.

k

int k

The third node.

l

int l

The fourth node.

m

int m

The fifth node.

n

int n

The sixth node.

Class edu.cmu.tetrad.search.utils.Tetrad

class Tetrad extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

i

int i

The first node.

j

int j

The second node.

k

int k

The third node.

l

int l

The fourth node.

Record Class edu.cmu.tetrad.search.utils.TetradInt

class TetradInt extends Record implements Serializable

Serialized Fields

i

int i

The field for the i record component.

j

int j

The field for the j record component.

k

int k

The field for the k record component.

l

int l

The field for the l record component.

Package edu.cmu.tetrad.search.work_in_progress

Class edu.cmu.tetrad.search.work_in_progress.Sextad

class Sextad extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

i

Node i

The first node in the sextad.

j

Node j

The second node in the sextad.

k

Node k

The third node in the sextad.

l

Node l

The fourth node in the sextad.

m

Node m

The fifth node in the sextad.

n

Node n

The sixth node in the sextad.

Package edu.cmu.tetrad.sem

Class edu.cmu.tetrad.sem.AdequacyReport

class AdequacyReport extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

fracNodesImproved

double fracNodesImproved

Represents the fraction

meanImprovement

double meanImprovement

Represents the mean improvement of nodes over a baseline metric in the context of an adequacy report.

This value indicates the average magnitude of improvement across all nodes, providing a summary measure for assessing overall performance enhancement.

mmd2

double mmd2

Represents the global Maximum Mean Discrepancy squared (MMD²) value between the real and simulated data distributions in the context of an adequacy report.

This metric provides a quantitative measure of how well the simulated data aligns with the real data, with smaller values indicating closer alignment. It is useful in evaluating the overall representational quality of the simulation process.

nodeSummaries

List<NodeAdequacySummary> nodeSummaries

Represents a collection of adequacy summaries for individual nodes within a model.

Each element in this list provides detailed metrics and performance insights for a specific node, including its name, parents, and performance improvements relative to a baseline. This field is used as part of the adequacy report to evaluate the performance and improvements of nodes in the context of the overall model.

This list is immutable and provides a comprehensive snapshot of per-node evaluation results.

Class edu.cmu.tetrad.sem.CVReport

class CVReport extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

fracNodesBeatBaseline

double fracNodesBeatBaseline

Fraction of non-root nodes whose OOS metric beats their respective baseline (R² > 0 for continuous; xent improvement > 0 for discrete). NaN if there are no non-root nodes.

meanOosMmd2

double meanOosMmd2

Mean OOS MMD² across folds. Each fold contributes one MMD² value computed between the observed held-out rows and data simulated by the model trained on the remaining folds.

meanOosR2

double meanOosR2

Mean OOS R² across continuous non-root nodes. Positive means the NN beats the marginal-mean baseline on average. NaN if there are no continuous non-root nodes.

meanOosXentImprovement

double meanOosXentImprovement

Mean OOS cross-entropy improvement (baseline − model) across discrete non-root nodes. Positive means the NN beats the marginal-frequency baseline on average. NaN if there are no discrete non-root nodes.

nodeSummaries

List<NodeCVSummary> nodeSummaries

Per-node OOS summaries, one per non-root node. Root nodes are excluded since they have no conditional mechanism to evaluate.

numFolds

int numFolds

Number of folds used.

Class edu.cmu.tetrad.sem.DagScorer

class DagScorer extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

covMatrix

ICovarianceMatrix covMatrix

The covariance matrix.

dag

Graph dag

The DAG.

dataSet

DataSet dataSet

The data set.

edgeCoef

Matrix edgeCoef

The edge coefficients.

errorCovar

Matrix errorCovar

The error covariance.

fml

double fml

The fml score.

implCovarMeasC

Matrix implCovarMeasC

The implied covariance matrix for the measured variables.

logDetSample

double logDetSample

The log determinant of the sample covariance matrix.

sampleCovar

Matrix sampleCovar

The sample covariance.

variables

List<Node> variables

The variables.

Class edu.cmu.tetrad.sem.EdgeStrengthResult

class EdgeStrengthResult extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

childName

String childName

Name of the child variable (head of the edge).

discreteChild

boolean discreteChild

true if the child variable is discrete.

drawsPerConfig

int drawsPerConfig

Number of draws of the child per configuration, for each of the two conditions.

klDivBits

double klDivBits

Mean over configurations and randomized draws of KL(P(Y | pa) ‖ P(Y | pa, X randomized)) in bits. NaN for continuous children.

klDivBitsSd

double klDivBitsSd

Standard deviation of EdgeStrengthResult.klDivBits across repeats; NaN if one repeat or continuous.

mmd2

double mmd2

Mean over parent configurations of MMD² between draws of the child with the configuration fixed and draws with the parent's input randomized. Continuous children are standardized by their observed SD first. Higher = stronger edge.

mmd2Sd

double mmd2Sd

Standard deviation of EdgeStrengthResult.mmd2 across repeats; NaN if one repeat.

nullMmd2

double nullMmd2

Refit-noise null: mean over refits of the same conditional MMD² between the child's original mechanism and a refit with the same parents under a new seed. This is the MMD² that training randomness alone produces. Shared by all edges into this child. NaN if no refits were run.

nullMmd2Sd

double nullMmd2Sd

Standard deviation of EdgeStrengthResult.nullMmd2 across refits; NaN if fewer than two.

nullRefits

int nullRefits

Number of refits the null is based on; 0 if skipped.

numRepeats

int numRepeats

Number of independent repeats the means and SDs are taken over.

parentName

String parentName

Name of the parent variable (tail of the edge).

simulatedN

int simulatedN

Number of observed parent configurations the measures were averaged over, per repeat.

varianceDiff

double varianceDiff

Mean over parent configurations of var(Y | pa, X randomized) − var(Y | pa), in the child's units squared. NaN for discrete children.

varianceDiffFrac

double varianceDiffFrac

EdgeStrengthResult.varianceDiff divided by the child's observed marginal variance, so it is comparable across children. NaN for discrete children.

varianceDiffFracSd

double varianceDiffFracSd

Standard deviation of EdgeStrengthResult.varianceDiffFrac across repeats; NaN if one repeat or discrete.

Class edu.cmu.tetrad.sem.GeneralizedSemIm

class GeneralizedSemIm extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

guaranteeIid

boolean guaranteeIid

Whether to guarantee that the IID is preserved when simulating data.

parameterValues

Map<String,Double> parameterValues

A map from freeParameters names to their values--these form the context for evaluating expressions. Variables do not appear in this list. All freeParameters are double-valued.

pm

GeneralizedSemPm pm

The wrapped PM, that holds all the expressions and structure for the model.

Class edu.cmu.tetrad.sem.GeneralizedSemPm

class GeneralizedSemPm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

errorNodes

List<Node> errorNodes

The error nodes.

errorsTemplate

String errorsTemplate

The stored template for error terms.

graph

SemGraph graph

The structural model graph that this sem parametric model is based on.

Cannot be null.

measuredNodes

List<Node> measuredNodes

The measured nodes.

namesToNodes

Map<String,Node> namesToNodes

A map from names to nodes, speedup.

nodeExpressions

Map<Node, Expression> nodeExpressions

The map from variable nodes to equations.

nodeExpressionStrings

Map<Node,String> nodeExpressionStrings

The String representations of equations that were set.

nodes

List<Node> nodes

The list of all nodes (unmodifiable).

Cannot be null.

parameterEstimationInitializationExpressions

Map<String, Expression> parameterEstimationInitializationExpressions

Distributions from which initial values for freeParameters are drawn.

parameterEstimationInitializationExpressionStrings

Map<String,String> parameterEstimationInitializationExpressionStrings

String representations of initial parameter distributions. A map from parameter names to expression strings.

parameterExpressions

Map<String, Expression> parameterExpressions

Distributions from which initial values for freeParameters are drawn.

parameterExpressionStrings

Map<String,String> parameterExpressionStrings

String representations of initial parameter distributions. A map from parameter names to expression strings.

parametersEstimationInitializationTemplate

String parametersEstimationInitializationTemplate

The stored template for freeParameters.

parametersTemplate

String parametersTemplate

The stored template for freeParameters.

parameterSubscript

Map<String,Integer> parameterSubscript

A map from names to nodes, speedup.

referencedNodes

Map<Node, Set<Node>> referencedNodes

The nodes of the model, variable nodes or error nodes, mapped to the other nodes that they are associated with.

referencedParameters

Map<String, Set<Node>> referencedParameters

The freeParameters in the model, mapped to the nodes that they are associated with. Each parameter may be associated with more than one node. When freeParameters are removed from an equation or error distribution, the associated nodes should be removed from the relevant set in this map, and if the set is empty, the parameter should be removed from the map. Also, before adding a parameter to this map, it must be checked whether a parameter by the same name already exists. If one such parameter by the same name already exists, that one should be used instead of the new one. This is needed both to avoid confusion and to allow freeParameters to be reused in different parts of the interface, creating equality constraints.

Cannot be null.

startsWithParametersEstimationInitializationTemplates

Map<String,String> startsWithParametersEstimationInitializationTemplates

A map from initial name strings to parameter templates.

startsWithParametersTemplates

Map<String,String> startsWithParametersTemplates

A map from initial name strings to parameter templates.

variableNames

List<String> variableNames

The list of variable names.

variableNodes

List<Node> variableNodes

The latent and measured nodes.

variablesTemplate

String variablesTemplate

The stored template for variables.

Class edu.cmu.tetrad.sem.Mapping

class Mapping extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

a

Matrix a

The 2D double array whose element at (i, j) to be manipulated.

Can't be null.

i

int i

The left-hand coordinate of a[i][j].

Any value.

j

int j

The right-hand coordinate of a[i][j].

Any value.

parameter

Parameter parameter

The parameter this mapping maps.

Can't be null.

semIm

ISemIm semIm

The SemIm for which this is a mapping.

Can't be null.

Class edu.cmu.tetrad.sem.NNEstimator

class NNEstimator extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

adequacyReport

AdequacyReport adequacyReport

The most recent adequacy report; null until NNEstimator.simulate(int) is called.

cvReport

CVReport cvReport

The most recent CV report; null until NNEstimator.crossValidate(int) is called.

dag

Graph dag

The DAG defining the factorization structure.

fittedSimulator

TrainedDagSimulatorGNM fittedSimulator

The fitted simulator; null until NNEstimator.fit() is called.

lastExtrapolationFraction

double lastExtrapolationFraction

Fraction of rows in the most recent simulation in which some node's continuous parents fell more than zWarn1 training SDs from their training mean; NaN until NNEstimator.simulate(int) is called.

observedData

DataSet observedData

The dataset to train on.

params

NNEstimatorParams params

The parameters used by this estimator.

simulatedData

DataSet simulatedData

The most recent simulated dataset; null until NNEstimator.simulate(int) is called.

Class edu.cmu.tetrad.sem.NNEstimatorParams

class NNEstimatorParams extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

edgeDrawsPerConfig

int edgeDrawsPerConfig

Number of draws of the child per parent configuration when computing edge strength (NNEstimator.computeEdgeStrength(String, String, int)). Each configuration is drawn this many times with the mechanism as fitted, and this many times again with the parent's input randomized. Default: 200.

edgeNullRefits

int edgeNullRefits

Number of refits used for the refit-noise null: the child's mechanism is retrained with the same parents under a new seed, and the same conditional MMD² is computed between the original and the refit. This is the MMD² produced by training randomness alone; an edge whose intervention MMD² does not clear it is not distinguishable from zero. Computed once per child and shared by all edges into that child. Set to 0 to skip. Default: 3.

edgeRepeats

int edgeRepeats

Number of independent repeats of the edge-strength computation, each with its own draw of parent configurations, noise, and randomized parent values. The reported values are the mean over repeats and the standard deviation across them is reported alongside. Default: 3.

epochs

int epochs

Training passes over the data per node. Default: 200.

hidden

int hidden

Hidden units in each node's network (single hidden layer). Default: 48.

l2

double l2

L2 weight decay. Default: 1e-4.

lr

double lr

SGD learning rate. Default: 0.01.

mmdFeatures

int mmdFeatures

Number of random Fourier features used by the MMD² approximation. Larger values give a more accurate estimate at the cost of speed. Default: 512.

mmdMaxRows

int mmdMaxRows

Maximum number of rows used when computing MMD². Set to a smaller value to keep adequacy computation fast on large datasets. Default: 5000.

mmdSeed

long mmdSeed

Random seed for the MMD² random feature approximation. Fix this to get reproducible adequacy scores. Default: 42.

seed

long seed

Random seed for the GNM simulator. Defaults to a time-based value so successive runs differ by default.

shuffleFolds

boolean shuffleFolds

If true, rows are randomly permuted (using NNEstimatorParams.seed) before being cut into k contiguous folds for cross-validation. If false, folds are contiguous blocks in file order, which is the right choice for serially dependent rows. Default: false.

Class edu.cmu.tetrad.sem.NodeAdequacySummary

class NodeAdequacySummary extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

baselineLoss

double baselineLoss

The loss value

discrete

boolean discrete

Indicates whether the node is discrete or continuous.

holdoutLoss

double holdoutLoss

The loss value obtained from the holdout set.

improvement

double improvement

The improvement in loss value from the baseline to the holdout set.

node

String node

The name or identifier of the node being evaluated within the model. This field uniquely represents the specific node whose adequacy and performance metrics are summarized in the containing class. It is typically used as a reference to evaluate its characteristics in relation to its parents and associated metrics. This value is immutable and set during the construction of the object.

parents

List<String> parents

List of parent nodes for the node being evaluated.

Class edu.cmu.tetrad.sem.NodeCVSummary

class NodeCVSummary extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

baselineMse

double baselineMse

Baseline MSE: variance of the child variable estimated from the full dataset. This is the MSE you would get by always predicting the marginal mean.

baselineXent

double baselineXent

Baseline cross-entropy: entropy of the empirical marginal distribution of the child variable. This is the cross-entropy you would get by always predicting the marginal class probabilities.

discreteChild

boolean discreteChild

true if the variable is discrete.

node

String node

Variable name.

numFolds

int numFolds

Number of folds used.

oosMse

double oosMse

Mean OOS MSE across folds: average of (observed - predicted)² on held-out rows. Uses zero-noise prediction (conditional mean estimate). NaN for discrete or root nodes.

oosR2

double oosR2

OOS R²: 1 - oosMse / baselineMse. Positive means the NN beats the mean baseline out of sample. NaN if either component is NaN.

oosXent

double oosXent

Mean OOS cross-entropy across folds on held-out rows. NaN for continuous or root nodes.

parents

List<String> parents

Parent variable names (empty for root nodes).

Class edu.cmu.tetrad.sem.ParamConstraint

class ParamConstraint extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

number

double number

The number of the constraint.

param2

Parameter param2

The first parameter.

semIm

SemIm semIm

The SEM.

type

ParamConstraintType type

The type of the constraint.

Class edu.cmu.tetrad.sem.Parameter

class Parameter extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

distribution

Distribution distribution

If this parameter is initialized randomly, the initial value is drawn from this distribution.

Cannot be null.

fixed

boolean fixed

True iff this parameter is fixed in estimation.

Any value.

initializedRandomly

boolean initializedRandomly

True iff this parameter should be initialized randomly.

Any value.

name

String name

The name of the parameter.

Cannot be null.

nodeA

Node nodeA

One of the anchor endpoints specifying the parameter this is.

Cannot be null.

nodeB

Node nodeB

One of the anchor endpoints specifying the parameter this is.

Cannot be null.

startingValue

double startingValue

If this parameter is either fixed or not initialized randomly, returns its starting value.

Any value.

type

ParamType type

The type of parameter--coefficient, covariance, or variance.

Cannot be null. Should be ParamType.VAR if nodeA != nodeB and ParamType.COVAR if nodeA == nodeB.

Class edu.cmu.tetrad.sem.ParameterPair

class ParameterPair extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

a

Parameter a

The first element of the ordered pair. Can be null.

May be null.

b

Parameter b

The second element of the ordered pair. Can be null.

May be null.

Class edu.cmu.tetrad.sem.PartialEdgeStrengthResult

class PartialEdgeStrengthResult extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

avgMarginalEffect

double avgMarginalEffect

Signed average marginal effect of the parent on the child: the average, over all held-out rows across the k folds, of the central finite difference (f(x + h) − f(x − h)) / (2h) of the fold's fitted mechanism with respect to the parent, with the other parents held at their observed values and h = 0.05 · SD(X). Uses each fold's full model on that fold's held-out rows, so it is an out-of-sample quantity on the same folds as PartialEdgeStrengthResult.partialR2. On the parent's original scale (child units per parent unit). NaN unless both parent and child are continuous.

avgMarginalEffectStd

double avgMarginalEffectStd

Standardized average marginal effect: PartialEdgeStrengthResult.avgMarginalEffect · SD(X) / SD(Y), with SDs taken from the observed data. Unit-free, so magnitudes are comparable across parents. NaN unless both parent and child are continuous.

childName

String childName

Name of the child variable (head of the edge).

discreteChild

boolean discreteChild

true if the child variable is discrete.

fracPositiveDeriv

double fracPositiveDeriv

Fraction of held-out rows on which the local derivative was strictly positive, among rows with a finite derivative. Values near 1 or 0 indicate a monotone fitted effect; intermediate values indicate the effect changes sign over the data range, in which case PartialEdgeStrengthResult.avgMarginalEffect is an average of opposing effects and should be read with care. NaN unless both parent and child are continuous.

numFolds

int numFolds

Number of CV folds used.

parentName

String parentName

Name of the parent variable (tail of the edge).

partialR2

double partialR2

Held-out R² of the full model minus held-out R² of the model with X removed from Y's parents, on the same k folds as the CV table. Positive = X adds predictive information beyond the other parents. NaN for discrete children.

partialXentImprovement

double partialXentImprovement

OOS cross-entropy improvement of predicting R from X vs. predicting the marginal residual distribution. For discrete children only. NaN for continuous children.

residualVariance

double residualVariance

Held-out MSE of the reduced model (Y predicted from its other parents, without X). Kept under its original field name for session compatibility. NaN for discrete children.

Class edu.cmu.tetrad.sem.PredictionPruneReport

class PredictionPruneReport extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

deletions

List<PredictionPruneReport.Deletion> deletions

The deletions.

numFolds

int numFolds

The number of folds used in the cross-validation.

prunedGraph

Graph prunedGraph

The pruned graph.

threshold

double threshold

The threshold used to determine whether an edge should be deleted.

Class edu.cmu.tetrad.sem.PredictionPruneReport.Deletion

class Deletion extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

childName

String childName

Name of the child variable (head of the deleted edge).

discreteChild

boolean discreteChild

true if the child variable is discrete.

meanImprovement

double meanImprovement

Fold-mean paired improvement from this parent at the time it was removed: ΔR² for a continuous child, Δ cross-entropy in nats for a discrete child.

parentName

String parentName

Name of the parent variable (tail of the deleted edge).

seImprovement

double seImprovement

Standard error of the improvement across folds.

step

int step

Elimination round within this child at which the edge fell (0-based).

tStat

double tStat

meanImprovement / seImprovement; NaN when SE is zero.

Class edu.cmu.tetrad.sem.SemEstimator

class SemEstimator extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

covMatrix

ICovarianceMatrix covMatrix

The covariance matrix used to estimate the SemIm. Note that the variables names in the covariance matrix must be in the same order as the variable names in the semPm.

dataSet

DataSet dataSet

The data set being estimated from (needed to calculate means of variables). May be null in which case means are set to zero.

estimatedSem

SemIm estimatedSem

The most recently estimated model, or null if no model has been estimated yet.

missingDataMoments

Map<String,double[]> missingDataMoments

When the data set has missing values, the EM estimates of the mean and standard deviation of each measured variable, by name; null otherwise.

numRestarts

int numRestarts

The number of restarts to use.

scoreType

ScoreType scoreType

The score type used to optimize the SEM.

semOptimizer

SemOptimizer semOptimizer

The algorithm that minimizes the fitting function for the SEM.

semPm

SemPm semPm

The SemPm containing the graph and the freeParameters to be estimated.

Class edu.cmu.tetrad.sem.SemEstimatorGibbsParams

class SemEstimatorGibbsParams extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

flatPrior

boolean flatPrior

Whether to use a flat prior.

numIterations

int numIterations

The number of iterations to run.

startIm

SemIm startIm

The initial SEM.

stretch

double stretch

The stretch factor.

tolerance

double tolerance

The tolerance for convergence.

Class edu.cmu.tetrad.sem.SemEvidence

class SemEvidence extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

manipulation

SemManipulation manipulation

A manipulation indicating how the bayes Im should be manipulated before updating.

proposition

SemProposition proposition

A proposition stating what we know for each variable.

Cannot be null.

semIm

SemIm semIm

Bayes IM that this is evidence for.

Class edu.cmu.tetrad.sem.SemIm

class SemIm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

cyclic

boolean cyclic

True just in case the graph for the SEM is cyclic.

cyclicChecked

boolean cyclicChecked

True just in case cyclicity has already been checked.

distributions

Map<Node, Distribution> distributions

Stores a distribution for each variable. Initialized to N(0, 1) for each.

edgeCoef

Matrix edgeCoef

Matrix of edge coefficients. edgeCoefC[i][j] is the coefficient of the edge from getVariableNodes().get(i) to getVariableNodes().get(j), or 0.0 if this edge is not in the graph. The values of these may be changed, but the array itself may not.

errCovar

Matrix errCovar

Matrix of error covariances. errCovar[i][j] is the covariance of the error term of getExoNodes().get(i) and getExoNodes().get(j), with the special case that errCovar[i][i] is the variance of getExoNodes.get(i). The values of these may be changed, but the array itself may not.

estimated

boolean estimated

True iff this SemIm is estimated.

fixedMappings

List<Mapping> fixedMappings

The list of fixed freeParameters (Unmodifiable). This must be in the same order as this.fixedParameters.

fixedParameters

List<Parameter> fixedParameters

The list of fixed freeParameters (Unmodifiable). This must be in the same order as this.fixedMappings.

freeMappings

List<Mapping> freeMappings

The list of freeMappings. This is an unmodifiable list. It is fixed (up to order) by the SemPm. This must be in the same order as this.freeParameters.

freeParameters

List<Parameter> freeParameters

The list of free freeParameters (Unmodifiable). This must be in the same order as this.freeMappings.

functions

Map<Node, ConnectionFunction> functions

Stores the connection functions of specified nodes.

implCovar

Matrix implCovar

Replaced by implCovarC. Please do not delete. Required for serialization backward compatibility.

meanParameters

List<Parameter> meanParameters

The list of mean freeParameters (Unmodifiable). This must be in the same order as variableMeans.

measuredNodes

List<Node> measuredNodes

The list of measured variableNodes from the semPm. (Unmodifiable.)

numRandomCalls

int numRandomCalls

Number of random calls.

parameterBoundsEnforced

boolean parameterBoundsEnforced

True iff setting freeParameters to out-of-bound values throws exceptions.

params

Parameters params

Parameters to help guide how values are chosen for freeParameters.

sampleCovarC

Matrix sampleCovarC

Replaced by sampleCovar. Please do not delete. Required for serialization backward compatibility.

sampleCovInv

Matrix sampleCovInv

The type of score to use for estimation.

sampleSize

int sampleSize

The sample size.

scoreType

ScoreType scoreType

Types of scores that yield a chi square value when minimized.

semPm

SemPm semPm

The Sem PM containing the graph and the freeParameters to be estimated. For now a defensive copy of this is not being constructed, since it is not used anywhere in the code except in the the constructor and in its accessor method. If somebody changes it, it's their own fault, but it won't affect this class.

standardErrors

double[] standardErrors

Stores the standard errors for the freeParameters. May be null.

variableMeans

double[] variableMeans

Means of variables. These will not be counted for purposes of calculating degrees of freedom, since the increase in dof is exactly balanced by a decrease in dof.

variableMeansStdDev

double[] variableMeansStdDev

Standard Deviations of means. Needed to calculate standard errors.

variableNodes

List<Node> variableNodes

The list of measured and latent variableNodes for the semPm. (Unmodifiable.)

variablesHash

Map<Node,Integer> variablesHash

The type of score to use for estimation.

Class edu.cmu.tetrad.sem.SemManipulation

class SemManipulation extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

manipulated

boolean[] manipulated

An array indicating whether each variable in turn is manipulated.

Cannot be null.

semIm

SemIm semIm

Bayes IM that this is evidence for.

Cannot be null.

Class edu.cmu.tetrad.sem.SemOptimizerEm

class SemOptimizerEm extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

errorParent

Node[] errorParent

Error parent of each node.

expectedCov

Matrix expectedCov

Expected covariance matrix.

graph

SemGraph graph

The SEM graph.

idxLatent

int[] idxLatent

Indices of the latent variables.

idxObserved

int[] idxObserved

Indices of the latent variables.

nodeParentsCov

double[][] nodeParentsCov

Covariance of each node with its parents.

numLatent

int numLatent

Number of observed and latent variables.

numObserved

int numObserved

Number of observed and latent variables.

numRestarts

int numRestarts

Number of restarts.

parents

int[][] parents

Indices of the parents of each node.

parentsCov

double[][][] parentsCov

Parents covariance matrix.

semIm

SemIm semIm

The SEM to optimize.

yCov

Matrix yCov

The sample covariance matrix.

yCovModel

Matrix yCovModel

Partitions of the modeled cov.

yzCovModel

Matrix yzCovModel

Partitions of the modeled cov.

zCovModel

Matrix zCovModel

Partitions of the modeled cov.

Class edu.cmu.tetrad.sem.SemOptimizerPowell

class SemOptimizerPowell extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

numRestarts

int numRestarts

The number of restarts.

Class edu.cmu.tetrad.sem.SemOptimizerRegression

class SemOptimizerRegression extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

numRestarts

int numRestarts

The number of restarts.

Class edu.cmu.tetrad.sem.SemOptimizerRicf

class SemOptimizerRicf extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

maxIters

int maxIters

Max RICF iterations.

numRestarts

int numRestarts

Represents the number of restarts allowed for the optimization process. This variable is used to control the maximum number of times the optimization algorithm can restart if it fails to converge to a solution in previous attempts. It is initialized to a default value of 1.

tolerance

double tolerance

RICF tolerance.

Class edu.cmu.tetrad.sem.SemOptimizerScattershot

class SemOptimizerScattershot extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

numRestarts

int numRestarts

The number of restarts to use.

Class edu.cmu.tetrad.sem.SemPm

class SemPm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

bIndex

int bIndex

The index of the most recent "B" parameter. (These are edge coefficients.)

Range >= 0.

graph

SemGraph graph

The structural model graph that this sem parametric model is based on.

Cannot be null.

mIndex

int mIndex

The index of the most recent "M" parameter. (These are means.)

Range >= 0.

nodes

List<Node> nodes

The list of all nodes (unmodifiable).

Cannot be null.

paramComparisons

Map<ParameterPair, ParamComparison> paramComparisons

The set of parameter comparisons.

Cannot be null.

parameters

List<Parameter> parameters

The list of Parameters (unmodifiable).

Cannot be null.

tIndex

int tIndex

The index of the most recent "T" parameter. (These are variance and covariance terms.)

Range >= 0.

variableNodes

List<Node> variableNodes

The list of variable nodes (unmodifiable).

Cannot be null.

Class edu.cmu.tetrad.sem.SemProposition

class SemProposition extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

semIm

SemIm semIm

Represents a final variable semIm.

values

double[] values

Represents a private final array of double values.

This variable is part of the SemProposition class in the Tetrad API. SemProposition is a class that represents a Proposition for a Bayes IM (Bayesian Inference Model). It allows for semantic checks when deserializing.

The values array contains the double values associated with the Proposition.

Class edu.cmu.tetrad.sem.SemUpdater

class SemUpdater extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

evidence

SemEvidence evidence

The evidence to be used in the update.

semIm

SemIm semIm

The SEM to be updated.

Class edu.cmu.tetrad.sem.StandardizedSemIm

class StandardizedSemIm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

edgeCoef

Matrix edgeCoef

The edge coefficient matrix of the model, a la SemIm. Note that this will normally need to be transposed, since [a][b] is the edge coefficient for a-->b, not b-->a. Sorry. History. THESE ARE PARAMETERS OF THE MODEL--THE ONLY PARAMETERS.

edgeParameters

Map<Edge,Double> edgeParameters

A map from edges in the graph to their coefficients. These are the only freeParameters in the model. This includes coefficients for directed as well as bidirected edges.

editingEdge

Edge editingEdge

The edge being edited.

errorCovar

Matrix errorCovar

The error covariance matrix of the model. i.e. [a][b] is the covariance of E_a and E_b, with [a][a] of course being the variance of E_a. THESE ARE NOT PARAMETERS OF THE MODEL; THEY ARE CALCULATED. Note that elements of this matrix may be Double.NaN; this indicates that these elements cannot be calculated.

errorVariances

Map<Node,Double> errorVariances

A map from error nodes in the graph to their error variances. These are not freeParameters in the model; their values are always calculated as residual variances, under the constraint that the variances of each variable must be 1.

implCovar

Matrix implCovar

The implied covariance matrix over all the variables.

implCovarMeas

Matrix implCovarMeas

The implied covariance matrix over the measured variables only.

range

StandardizedSemIm.ParameterRange range

The range of the parameter being edited.

sampleSize

int sampleSize

The sample size for the model.

semGraph

SemGraph semGraph

The graph of the model. Stored internally because it must be ensured that the error terms are showing.

semPm

SemPm semPm

The SEM model.

Class edu.cmu.tetrad.sem.StandardizedSemIm.ParameterRange

class ParameterRange extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

coef

double coef

The coefficient value for which the range is needed.

edge

Edge edge

The edge for which the range is needed.

high

double high

The high end of the range to which the coefficient value may be adjusted.

low

double low

The low end of the range to which the coefficient value may be adjusted.

Class edu.cmu.tetrad.sem.TrainedDagSimulatorGNM

class TrainedDagSimulatorGNM extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

dag

Graph dag

A final variable representing a Graph object.

data

DataSet data

A final variable representing a DataSet object.

isDiscrete

boolean[] isDiscrete

A final variable representing a boolean array.

mechanisms

edu.cmu.tetrad.sem.TrainedDagSimulatorGNM.Mechanism[] mechanisms

A final variable representing an array of Mechanism objects. Each Mechanism corresponds to a node in the DAG and encapsulates the learned model for that node.

nodeReports

List<TrainedDagSimulatorGNM.NodeReport> nodeReports

A thread-safe list that holds NodeReport objects. This list is used to store reports related to nodes in the system. It is synchronized to ensure safe access and modification in a concurrent environment.

params

TrainedDagSimulatorGNM.Params params

A final variable representing a Params object. It encapsulates parameters and settings for the simulation process. The immutability of this variable ensures that the reference to the Params cannot be altered once assigned.

variables

List<Node> variables

A final variable representing a List of Node objects.

Class edu.cmu.tetrad.sem.TrainedDagSimulatorGNM.NodeReport

class NodeReport extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

discreteChild

boolean discreteChild

Whether the node represents a discrete variable.

mseTrain

double mseTrain

Mean Squared Error (MSE) for the training dataset associated with the node. This metric is relevant only for nodes representing continuous variables. If the node is a discrete variable, this value will be NaN.

node

String node

Node identifier.

numLevels

int numLevels

Number of discrete levels for the node. This metric is relevant only for nodes representing discrete variables. If the node is a continuous variable, this value will be 0.

parents

List<String> parents

List of parent nodes for the current node.

residualMean

double residualMean

Mean and standard deviation of residuals for the training dataset associated with the node. This metric is relevant only for nodes representing continuous variables. If the node is a discrete variable, these values will be NaN.

residualSd

double residualSd

Standard deviation of residuals for the training dataset associated with the node. This metric is relevant only for nodes representing continuous variables. If the node is a discrete variable, this value will be NaN.

trainingRowsUsed

int trainingRowsUsed

Number of training rows used for the node.

xentTrain

double xentTrain

Cross-entropy loss for the training dataset associated with the node. This metric is relevant only for nodes representing discrete variables. If the node is a continuous variable, this value will be NaN.

Class edu.cmu.tetrad.sem.TrainedDagSimulatorGNM.Params

class Params extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

batchSize

int batchSize

Represents the number of samples to be processed together in a single batch during training. This variable is commonly used in machine learning and deep learning applications to control the size of data subsets passed to the model for each training iteration.

bootstrapRoots

boolean bootstrapRoots

Indicates whether bootstrap sampling should be used when initializing roots during the execution of certain algorithms. When set to true, the system will use bootstrap sampling to initialize roots; otherwise, it will not use bootstrap sampling.

epochs

int epochs

Specifies the number of training iterations or epochs, which represent one complete pass through the entire training dataset during model training. This value determines how many times the model will see the entire dataset for learning and optimization. A higher number of epochs typically allows the model to train longer and potentially achieve better performance, but it may also increase the risk of overfitting. It is important to tune this parameter according to the dataset and problem at hand. Default value: 200

hidden

int hidden

Specifies the default number of hidden units in a single layer of the model. This parameter is used to define the size of a hidden layer when no explicit layer configuration is provided through the hiddenLayers parameter.

hiddenLayers

int[] hiddenLayers

Specifies the layer configuration of a neural network by defining the number of hidden units for each layer. This variable is used to explicitly set the size and number of hidden layers in the model. If the value is null or an empty array, a default configuration with a single hidden layer, as specified by the hidden parameter, will be used instead. Each element in the array represents the number of neurons for one hidden layer, ordered sequentially from the first to the last hidden layer.

l2

double l2

L2 regularization parameter used to prevent overfitting during the training process. This value controls the penalty applied to the magnitude of model weights, encouraging smaller weights and promoting generalization.

lambdaParents

double lambdaParents

A parameter representing the regularization strength applied to parent nodes in a learning model. It is a double value used to control the contribution of parent nodes during training. A higher value increases the penalty, potentially discouraging overfitting, whereas a lower value reduces the penalty, allowing for greater flexibility in modeling the parent nodes' influence.

lr

double lr

Specifies the learning rate used in the optimization algorithm during training. The learning rate determines the step size at which the optimization algorithm adjusts the model parameters in response to the estimated gradient during training. A smaller learning rate may result in slower convergence but can offer more precise adjustments to model parameters, while a larger learning rate can speed up convergence but risks overshooting optimal parameter values or failing to converge. Default value: 0.01

maxDiscreteLevels

int maxDiscreteLevels

The maximum number of discrete levels allowed for a variable or feature in the model or algorithm. It is used to impose a limit on the granularity of discrete variables, ensuring computational efficiency and preventing excessively fine categorizations.

maxResidualStrata

int maxResidualStrata

The maximum number of residual strata to consider for stratification. This parameter controls the maximum number of distinct strata that residuals can be grouped into based on discrete parent variables. It helps manage memory usage and computational complexity, especially in large datasets.

seed

long seed

The initial seed value used for random number generation or other computational purposes within the application. This value can be customized to control repeatability in scenarios like machine learning model training, simulations, or other processes requiring stochastic behaviors.

stratifyResidualsByDiscreteParents

boolean stratifyResidualsByDiscreteParents

Indicates whether residuals should be stratified based on discrete parent variables. When set to true, the model will group residuals into strata according to the distinct values of discrete parent variables. This setting is typically used in models involving discrete data to provide finer granularity in analysis or computation.

zWarn1

double zWarn1

A threshold parameter used for controlling or warning about a specific condition or operation within the application. The exact purpose and usage are dependent on the broader context of the containing class. The value is initialized to 4.0 by default.

zWarn2

double zWarn2

A configurable parameter used to define a specific warning threshold value. This parameter can be utilized in various computations or validations where such a threshold is required.

Class edu.cmu.tetrad.sem.TrainedDagSimulatorGNM.SimResult

class SimResult extends Object implements Serializable

serialVersionUID:

1L

Serialized Fields

cont

double[][] cont

A two-dimensional array representing continuous values for all variables in a simulation result. This array includes numerical data corresponding to continuous variables, while discrete columns are also present but are considered irrelevant in this context. Each row typically corresponds to a sample, and each column corresponds to a variable.

disc

int[][] disc

Discrete codes for all variables in a simulation result. This array includes numerical data corresponding to discrete variables, while continuous columns are also present but are considered irrelevant in this context. Each row typically corresponds to a sample, and each column corresponds to a variable.

nSamples

long nSamples

Number of samples simulated in this result.

rowsExceedWarn1

long rowsExceedWarn1

Number of simulated rows in which at least one node's continuous parents exceeded TrainedDagSimulatorGNM.SimResult.zWarn1 in training z-units, i.e. rows where some mechanism was asked to extrapolate.

trueDag

Graph trueDag

Graph representing the true causal structure of the simulation. This field contains a Graph object representing the true causal structure of the simulation. It is used to compare against the simulated structure and assess the accuracy of the simulation.

variables

List<Node> variables

List of variables in the simulation result. This field contains a list of Node objects representing the variables in the simulation. Each Node corresponds to a variable in the simulation, and the list order reflects the order of variables in the simulation result.

zExceedWarn1

long[] zExceedWarn1

Tracks the count of occurrences where a specific variable index exceeds a certain z-score warning threshold during simulation. These counts are indexed by variable.

This field is primarily used to support warnings and validations in simulation reports where z-score thresholds are monitored. The array size matches the number of variables being simulated, allowing each index to correspond to a specific variable.

Modifications to this field are expected to occur internally within simulation processes that monitor and track z-score exceedance events.

zExceedWarn2

long[] zExceedWarn2

Tracks the count of occurrences where a specific variable index exceeds a certain z-score warning threshold during simulation. These counts are indexed by variable.

This field is primarily used to support warnings and validations in simulation reports where z-score thresholds are monitored. The array size matches the number of variables being simulated, allowing each index to correspond to a specific variable.

Modifications to this field are expected to occur internally within simulation processes that monitor and track z-score exceedance events.

zWarn1

double zWarn1

Tracks the count of occurrences where a specific variable index exceeds a certain z-score warning threshold during simulation. These counts are indexed by variable.

This field is primarily used to support warnings and validations in simulation reports where z-score thresholds are monitored. The array size matches the number of variables being simulated, allowing each index to correspond to a specific variable.

Modifications to this field are expected to occur internally within simulation processes that monitor and track z-score exceedance events.

zWarn2

double zWarn2

Tracks the count

Package edu.cmu.tetrad.study.gene.tetrad.gene.graph

Class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ActiveLagGraph

class ActiveLagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

lagGraph

LagGraph lagGraph

Underlying graph representing the update graph.

Class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraph

class ManualLagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

lagGraph

BasicLagGraph lagGraph

The lag graph.

Class edu.cmu.tetrad.study.gene.tetrad.gene.graph.ManualLagGraphParams

class ManualLagGraphParams extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - if any.

ClassNotFoundException - if any.

Serialized Fields

mlag

int mlag

The maximum lag of the lag graph.

varsPerInd

int varsPerInd

The number of variables per individual.

Class edu.cmu.tetrad.study.gene.tetrad.gene.graph.StoredLagGraphParams

class StoredLagGraphParams extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

filename

String filename

The filename of the stored lag graph.

Package edu.cmu.tetrad.study.gene.tetrad.gene.history

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasalInitializer

class BasalInitializer extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

basalExpression

double basalExpression

The average expression level that all unregulated genes are initialized to.

initStDev

double initStDev

The standard deviation of a normal distribution N(basalExpression, sem.D.) that random initial values for unregulated genes are set to.

updateFunction

UpdateFunction updateFunction

The update function this is initializing for.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.BasicLagGraph

class BasicLagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

connectivity

SortedMap<String, SortedSet<LaggedFactor>> connectivity

For each factor, stores the set of lagged factors which map into it. (Maps Strings to SortedSets of Strings.) This is the main data structure for the graph.

locations

Map<String,PointXy> locations

Stores the locations of the points for a directed graph.

maxLagAllowable

int maxLagAllowable

The maximum allowable lag. edges may not be added with lags greater than this. The value must be >= 1.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanFunction

class BooleanFunction extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

lookupTable

boolean[] lookupTable

The stored boolean function. The order of the rows (for the given parents array, for two parents) is 00, 01, 10, 11, and so on for higher numbers of parents.

parents

IndexedParent[] parents

The array of parents for the stored boolean function.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.BooleanGlassFunction

class BooleanGlassFunction extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

basalExpression

double basalExpression

The basalExpression for determining whether history expression levels should be mapped to "true" or "false" for purposes of looking up output values in the Boolean function table.

booleanFunctions

BooleanFunction[] booleanFunctions

Stores a boolean function for each factor from a preselected set of lagged factors to the given factor.

booleanInfluenceRate

double booleanInfluenceRate

The rate at which the F function (with outputs -1 and +1) affects the update for a gene.

connectivity

IndexedLagGraph connectivity

The indexed connectivity "snapshot" of the lag graph.

decayRate

double decayRate

The rate at which expression levels for a gene tend to return to basal level.

errorDistributions

Distribution[] errorDistributions

Error distributions from which errors are drawn for each of the factors.

lowerBound

double lowerBound

The lower bound for expression levels. Expression levels that wander below this bound will be set to this bound.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.DishModel

class DishModel extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

dishBumps

double[] dishBumps

An array of dish bumps for each dish.

dishBumpStDev

double dishBumpStDev

The standard deviation of the normal distribution from which dish bump values are drawn, in percent. The distribution has a mean of 100%.

dishNumber

int dishNumber

The number of the getModel dish.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.GeneHistory

class GeneHistory extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

dishModel

DishModel dishModel

A model of the differences in expression levels due to the particular dish a sample is taken from.

historyArray

double[][] historyArray

A history of time slices of values for each factor, extending back as far as is necessary for the update function to be applied properly (that is, from maxlag up to 0, the getModel time step). Note that the firs subscript is the time slice, whereas the second subscript is the expression level for each gene.

initializer

Initializer initializer

The initializer for the history.

initSync

boolean initSync

Indicates whether initialization should be synchronized or not. If it's synchronized, then the same (or almost the same) set of initial random values are used each time the initialize() method is called. Otherwise, a new set of random values is chosen each time. Note that this is a "first pass" attempt at "shocking" the simulated cells.

step

int step

The getModel time step, which is the number of steps after the initialization period. In other words, time step 0 is the first update step after the initialization, or the first step at which the Glass updating function has been applied. (Markov process.)

syncInitialization

double[][] syncInitialization

A stored copy of the initial values for the history array, to be used if synchronized initialization is desired. If synchonized initialization is selected, then on the first pass through the initialization method, this array is calculated, and for each individual simulated, the history array for that individual is initialized using values from this array.

updateFunction

UpdateFunction updateFunction

The update function for the history.

updatePeriods

int[] updatePeriods

To simulate asynchronous updating, update periods for each factor are allowed to be different. (Note: this was a brilliant idea somebody had a long time ago that has never yet been used. jdramsey 2/22/02)

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedConnectivity

class IndexedConnectivity extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

factors

List<String> factors

The factors in the graph, in the order that they are used.

parents

IndexedParent[][] parents

The graph that this "snapshot" of indexedConnectivity was taken from.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedLagGraph

class IndexedLagGraph extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

factors

List<String> factors

The factors in the graph, in the order that they are used.

parents

IndexedParent[][] parents

The graph that this "snapshot" of indexedLagGraph was taken from.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.IndexedParent

class IndexedParent extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

index

int index

The index of the parent.

lag

int lag

The lag of the parent.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedEdge

class LaggedEdge extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

factor

String factor

The name of the factor.

laggedFactor

LaggedFactor laggedFactor

The lagged factor.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.LaggedFactor

class LaggedFactor extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - if any.

ClassNotFoundException - if any.

Serialized Fields

factor

String factor

The name of the factor.

lag

int lag

The number of time steps back for the lagged factor.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.LinearFunction

class LinearFunction extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - an ObjectInputStream object

Throws:

IOException - if any.

ClassNotFoundException - if any.

Serialized Fields

polynomialFunction

PolynomialFunction polynomialFunction

The wrapped polynomial function that's doing all the work.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.Polynomial

class Polynomial extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

terms

List<PolynomialTerm> terms

The terms of the polynomial.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialFunction

class PolynomialFunction extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream s)
                 throws IOException,
ClassNotFoundException

Adds semantic checks to the default deserialization method. This method must have the standard signature for a readObject method, and the body of the method must begin with "s.defaultReadObject();". Other than that, any semantic checks can be specified and do not need to stay the same from version to version. A readObject method of this form may be added to any class, even if Tetrad sessions were previously saved out using a version of the class that didn't include it. (That's what the "s.defaultReadObject();" is for. See J. Bloch, Effective Java, for help.

Parameters:

s - The input stream from which this object is being deserialized.

Throws:

IOException - If any.

ClassNotFoundException - If any.

Serialized Fields

connectivity

IndexedLagGraph connectivity

The "snapshot" indexed connectivity of the initial lag graph.

errorDistributions

Distribution[] errorDistributions

Error distributions from which errors are drawn for each of the factors.

polynomials

Polynomial[] polynomials

The polynomials of each factor given its parents.

Class edu.cmu.tetrad.study.gene.tetrad.gene.history.PolynomialTerm

class PolynomialTerm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

coefficient

double coefficient

The coefficient of the term.

variables

int[] variables

The variables of the term.

Package edu.cmu.tetrad.study.gene.tetrad.gene.simulation

Class edu.cmu.tetrad.study.gene.tetrad.gene.simulation.MeasurementSimulator

class MeasurementSimulator extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

cellNumber

int cellNumber

The cellNumber variable represents the number of a cell. It is a private integer variable with an initial value of -1.

dishNumber

int dishNumber

The dishNumber variable stores the number of a dish. It is an integer value and is initially set to -1.

history

GeneHistory history

The history that will be used to simulate the data.

measuredData

double[][][] measuredData

Array variable to store measured data.

This variable is a 3-dimensional array of type double to store measured data. It is used to store data collected from various measures or experiments. The first dimension represents the measure index, the second dimension represents the sample index within the measure, and the third dimension represents the data value.

The structure of the array is as follows:

• The first dimension represents the measure index, ranging from 0 to n-1.
• The second dimension represents the sample index within the measure, ranging from 0 to m-1.
• The third dimension represents the data value, ranging from 0 to k-1.

The data values in the array are of type double, allowing for the storage of decimal values. The array dimensions and size may vary based on the specific application and requirements.

Access to this variable is restricted to the private scope to ensure encapsulation and proper data management.

Usage example: measuredData[1][2][3]

parameters

Parameters parameters

The parameters for this simulation.

rawData

double[][][] rawData

This variable stores raw data in a three-dimensional array.

The first dimension represents the rows in the data.

The second dimension represents the columns in the data.

The third dimension represents additional dimensions for the data, which can be used for organizing multidimensional data.

The values stored in this array are of type double.

Access to this variable is private, meaning it can only be accessed from within the class it is declared in.

Modifying this variable should be done with caution, as it contains sensitive raw data.

timeSteps

int[] timeSteps

Represents an array of time steps.

This variable is used to store an array of integers representing different time steps.

Package edu.cmu.tetrad.study.gene.tetradapp.model

Class edu.cmu.tetrad.study.gene.tetradapp.model.GenePm

class GenePm extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

lagGraph

LagGraph lagGraph

The wrapped lag workbench.

Class edu.cmu.tetrad.study.gene.tetradapp.model.MeasurementSimulatorParams

class MeasurementSimulatorParams extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

includeDishAndChipVariables

boolean includeDishAndChipVariables

Whether to include dish and chip variables in the simulation.

simulator

MeasurementSimulator simulator

The wrapped measurement simulator.

Package edu.cmu.tetrad.util

Class edu.cmu.tetrad.util.DefaultTetradLoggerConfig

class DefaultTetradLoggerConfig extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

active

Set<String> active

The event ids that are currently active.

events

List<TetradLoggerConfig.Event> events

The events that are supported.

Class edu.cmu.tetrad.util.DefaultTetradLoggerConfig.DefaultEvent

class DefaultEvent extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

description

String description

The description of the event.

id

String id

The id of the event.

Class edu.cmu.tetrad.util.Matrix

class Matrix extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

data

org.ejml.simple.SimpleMatrix data

The `data` variable represents a matrix structure used for numerical computations and data representation. It is an immutable instance of the `SimpleMatrix` class that supports various matrix operations.

m

int m

The number of rows.

matrixView

MView matrixView

The view of the matrix. This is used to allow a subset of the matrix to be viewed and set.

n

int n

The number of columns.

Class edu.cmu.tetrad.util.MView

class MView extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

matrix

Matrix matrix

Represents the underlying Matrix object associated with this MatrixView. This field stores the original matrix or a reference to it, which serves as the basis for any operations or sub-views created by this MatrixView instance. It can be null if the MatrixView is not initialized with a specific matrix.

matrixView

MView matrixView

Represents a view of a matrix, typically used to access or modify a subset of the rows and columns of an original matrix or another matrix view. This variable holds a reference to an immutable object of type MView. The matrixView object can include functionalities such as retrieving specific elements, updating values, or creating further sub-views of its data.

viewCols

int[] viewCols

Represents the columns of the associated matrix view. Each element in this array corresponds to an index of a column in the original matrix that is part of the view. This array defines the mapping of columns from the original matrix to the matrix view. It is immutable.

viewRows

int[] viewRows

Represents an array of row indices included in the matrix view. This array determines which rows from the original matrix are part of the current view. Immutable and specific to the representation of rows in a submatrix.

Class edu.cmu.tetrad.util.Parameters

class Parameters extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

overriddenParameters

Map<String,Object> overriddenParameters

The overridden parameters.

parameters

Map<String,Object[]> parameters

The parameters.

usedParameters

Set<String> usedParameters

The used parameters.

Class edu.cmu.tetrad.util.PartialCorrelationPdf

class PartialCorrelationPdf extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

constant

double constant

The aggregate value of the constant expression in the distribution function for zero partial correlation.

k

int k

Number of compared variables--that is, 2 + (#conditioning variables).

n

int n

Number of data points in the sample.

outsideExp

double outsideExp

The power to which the variable expression is raised in the distribution function for zero partial correlation.

Class edu.cmu.tetrad.util.PointXy

class PointXy extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

x

int x

The x coordinate.

y

int y

The y coordinate.

Class edu.cmu.tetrad.util.TetradLogger.EmptyConfig

class EmptyConfig extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

active

boolean active

Represents the activation status of an event in the logger configuration.

Class edu.cmu.tetrad.util.TetradLoggerEvent

class TetradLoggerEvent extends EventObject implements Serializable

Serialized Fields

config

TetradLoggerConfig config

The config associated with the event, may be null.

Class edu.cmu.tetrad.util.Vector

class Vector extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

data

org.ejml.simple.SimpleMatrix data

The data.

Class edu.cmu.tetrad.util.Version

class Version extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

incrementalRelease

int incrementalRelease

The incremental release number. In release a.b.c-d, d. This number increases without bound until the next major version, minor version, or minor subversion release, at which point is goes back to zero. If it is zero, release a.b.c.dx may be referred to as a.b.c.

With maven snapshots the incremental release number refers to the snapshot build date. If this field is SNAPSHOT it is set to max int

Range greater than or equal to 0.

majorVersion

int majorVersion

The major version number. In release a.b.c-d, a. At time of creating this class, it's 4, and the minor version is 3. This should increase only for truly substantial and essentially complete new releases of Tetrad.

Range greater than or equal to 0.

minorSubversion

int minorSubversion

The minor release number. In release a.b.c-d, c. This number increases without bound until the next major or minor release, at which point it goes back to zero.

Range greater than or equal to 0.

minorVersion

int minorVersion

The minor version number. In release a.b.c-d, b. This number increases without bound until the next major release, at which point it goes back to zero.

Range greater than or equal to 0.

Package edu.cmu.tetrad.util.dist

Class edu.cmu.tetrad.util.dist.Beta

class Beta extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

Ibid.

beta

double beta

Ibid.

Class edu.cmu.tetrad.util.dist.ChiSquare

class ChiSquare extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

df

double df

The stored degrees of freedom. Needed because the wrapped distribution does not provide getters for its parameters.

Class edu.cmu.tetrad.util.dist.Discrete

class Discrete extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

p

double[] p

The probabilities of the different values.

Class edu.cmu.tetrad.util.dist.Exponential

class Exponential extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

lambda

double lambda

The rate parameter.

Class edu.cmu.tetrad.util.dist.Gamma

class Gamma extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

alpha

double alpha

The shape parameter.

lambda

double lambda

The rate parameter.

Class edu.cmu.tetrad.util.dist.GaussianPower

class GaussianPower extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

name

String name

The name.

power

double power

The power.

sd

double sd

The standard deviation of the Gaussian distribution.

Class edu.cmu.tetrad.util.dist.Indicator

class Indicator extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

p

double p

The probability of returning 1.

Class edu.cmu.tetrad.util.dist.LogNormal

class LogNormal extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

sd

double sd

The standard deviation.

Class edu.cmu.tetrad.util.dist.MixtureOfGaussians

class MixtureOfGaussians extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

a

double a

The mixing parameter.

mean1

double mean1

The mean of the first Gaussian.

mean2

double mean2

The mean of the second Gaussian.

sd1

double sd1

The standard deviation of the first Gaussian.

sd2

double sd2

The standard deviation of the second Gaussian.

Class edu.cmu.tetrad.util.dist.Normal

class Normal extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

mean

double mean

The mean of the distribution.

sd

double sd

The standard deviation of the distribution.

Class edu.cmu.tetrad.util.dist.Poisson

class Poisson extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

mean

double mean

The mean of the Poisson distribution.

Class edu.cmu.tetrad.util.dist.SingleValue

class SingleValue extends Object implements Serializable

serialVersionUID:

23L

Serialized Fields

value

double value

Represents a single value in a statistical distribution.

Class edu.cmu.tetrad.util.dist.Split

class Split extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

a

double a

Represents the variable 'a' in the Split distribution.

b

double b

A private variable representing the value of `b`.

Class edu.cmu.tetrad.util.dist.TruncatedNormal

class TruncatedNormal extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

high

double high

The standard devision of the distribution.

low

double low

The standard devision of the distribution.

mean

double mean

The mean of the distribution.

sd

double sd

The standard devision of the distribution.

Class edu.cmu.tetrad.util.dist.Uniform

class Uniform extends Object implements Serializable

serialVersionUID:

23L

Serialization Methods

readObject

private void readObject(ObjectInputStream in)
                 throws IOException,
ClassNotFoundException

Reads the object from the specified ObjectInputStream. This method is used during deserialization to restore the state of the object.

Parameters:

in - The ObjectInputStream to read the object from.

Throws:

IOException - If an I/O error occurs.

ClassNotFoundException - If the class of the serialized object cannot be found.

writeObject

private void writeObject(ObjectOutputStream out)
                  throws IOException

Writes the object to the specified ObjectOutputStream.

Parameters:

out - The ObjectOutputStream to write the object to.

Throws:

IOException - If an I/O error occurs.

Serialized Fields

a

double a

The lower bound of the range from which numbers are drawn uniformly.

b

double b

The upper bound of the range from which numbers are drawn uniformly.

Package edu.pitt.isp.sverchkov.data

Class edu.pitt.isp.sverchkov.data.AdTree

class AdTree extends edu.pitt.isp.sverchkov.data.AdTreeHelper implements Serializable

Serialized Fields

attributeLookup

Map<A,Integer> attributeLookup

The attribute lookup.

attributes

List<A> attributes

The attributes.

root

edu.pitt.isp.sverchkov.data.AdTreeHelper.CountNode root

The root of the tree

values

List<AdTree<A,V>.edu.pitt.isp.sverchkov.data.AdTree.VHelper> values

The values.

Class edu.pitt.isp.sverchkov.data.AdTreeHelper.CountNode

class CountNode extends Object implements Serializable

Serialized Fields

attr

int attr

The attribute of this node.

count

int count

The number of instances in the data set.

vary

edu.pitt.isp.sverchkov.data.AdTreeHelper.VaryNode[] vary

The children of this node.

Class edu.pitt.isp.sverchkov.data.AdTreeHelper.VaryNode

class VaryNode extends Object implements Serializable

Serialized Fields

mcv

int mcv

The most common value of the attribute.

values

edu.pitt.isp.sverchkov.data.AdTreeHelper.CountNode[] values

The values of the attribute.