Uses of Package
edu.cmu.tetrad.data

Packages that use edu.cmu.tetrad.data

Package	Description
edu.cmu.tetrad.algcomparison
edu.cmu.tetrad.algcomparison.algorithm
edu.cmu.tetrad.algcomparison.algorithm.continuous.dag
edu.cmu.tetrad.algcomparison.algorithm.multi
edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag
edu.cmu.tetrad.algcomparison.algorithm.oracle.pag
edu.cmu.tetrad.algcomparison.algorithm.other
edu.cmu.tetrad.algcomparison.algorithm.pairwise
edu.cmu.tetrad.algcomparison.independence
edu.cmu.tetrad.algcomparison.score
edu.cmu.tetrad.algcomparison.simulation
edu.cmu.tetrad.algcomparison.statistic
edu.cmu.tetrad.algcomparison.sweep
edu.cmu.tetrad.algcomparison.utils
edu.cmu.tetrad.bayes
edu.cmu.tetrad.calculator
edu.cmu.tetrad.calibration
edu.cmu.tetrad.classify
edu.cmu.tetrad.data
edu.cmu.tetrad.data.audit
edu.cmu.tetrad.data.missing
edu.cmu.tetrad.data.simulation
edu.cmu.tetrad.estimate.v1
edu.cmu.tetrad.graph
edu.cmu.tetrad.hybridcg
edu.cmu.tetrad.regression
edu.cmu.tetrad.search	This package contains classes for causal graph search algorithms.
edu.cmu.tetrad.search.blocks
edu.cmu.tetrad.search.cdnod_pag
edu.cmu.tetrad.search.harness
edu.cmu.tetrad.search.harness.tsbi
edu.cmu.tetrad.search.harness.tsc
edu.cmu.tetrad.search.is
edu.cmu.tetrad.search.mimic
edu.cmu.tetrad.search.rlcd
edu.cmu.tetrad.search.score	This package contains classes for scoring causal graph models.
edu.cmu.tetrad.search.test	This package contains classes for testing causal graph search algorithms.
edu.cmu.tetrad.search.unmix
edu.cmu.tetrad.search.utils	This package contains utility classes for causal graph search algorithms.
edu.cmu.tetrad.search.work_in_progress	A package for algorithms that are not ready for prime time.
edu.cmu.tetrad.sem
edu.cmu.tetrad.simulation
edu.cmu.tetrad.study.missingness
edu.cmu.tetrad.study.performance
edu.cmu.tetrad.util
edu.pitt.csb.mgm
edu.pitt.csb.stability
edu.pitt.dbmi.algo.bayesian.constraint.search

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.continuous.dag

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.multi

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.oracle.cpdag

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.oracle.pag

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.other

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.algorithm.pairwise

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.independence

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.score

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.simulation

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.statistic

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.sweep

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.algcomparison.utils

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.bayes

Class	Description
DataFilter	Interface implemented by classes whose purpose is to generate modifications of data sets.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DiscreteVariable	Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.
Simulator	Created by jdramsey on 12/22/15.
VariableSource	Inteface implemented by classes, instantiations of which are associated with lists of variables.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.calculator

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.calibration

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.classify

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DiscreteVariable	Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.data

Class	Description
AbstractVariable	Base class for variable specifications for DataSet.
BoxDataSet	Wraps a DataBox in such a way that mixed data sets can be stored.
CellTable	Represents a cell table that stores the values of the cells in a table of arbitrary dimension, for use, e.g., in the context of a contingency table--e.g.
ContinuousVariable	Represents a real-valued variable.
CorrelationMatrix	Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
CorrelationMatrixOnTheFly	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
CovarianceMatrixOnTheFly	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataBox	Stores a 2D array of data.
DataFilter	Interface implemented by classes whose purpose is to generate modifications of data sets.
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataModelList	Stores a list of data models and keeps track of which one is selected.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.
DelimiterType	Type-safe enum of delimiter types for parsing data.
DiscreteDiscretizationSpec	Specifies how a column (continuous or discrete) should be discretized.
DiscreteVariable	Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.
DiscreteVariableType	Type-safe enum of discrete variable types.
DiscretizationSpec	A continuous or discrete discretization spec (see).
Discretizer.Discretization	A discretization specification for a continuous variable.
EmCovarianceEstimator.Result	The result of an EM run: the estimated mean and covariance, together with convergence information.
ICovarianceMatrix	Interface for covariance matrices.
IndependenceFacts	Stores a list of independence facts.
JoinDatasets	Joins two tabular data sets on a key, in the manner of a database join: each row of the left data set is looked up in the right data set by its key value(s), and the right data set's non-key columns are appended to it.
JoinDatasets.JoinType	Which unmatched rows to keep.
JoinDatasets.Result	The joined data set and a findings-only report.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.
KnowledgeEdge	Implements a knowledge edge X-->Y as a simple ordered pair of strings.
KnowledgeGroup	Represents a "Other Group" in Knowledge, which can be understood as: Group1 -> Group2 where there are edges between all members of Group1 to Group2.
KnowledgeTierStructure	An additional, named tier structure over (a subset of) the variables of a Knowledge object, independent of the main temporal tiers and of every other tier structure.
KnowledgeTransferable	Interface implemented by classes that are capable of participating in the transfer of knowledge objects.
LogTransformSpec	A logarithmic transform to apply to a single variable: the direction (log or unlog), the offset a, and the base.
LongToWide	Reshapes a long-format data set (one row per unit per occasion, e.g., one row per student per assessment) into a wide-format data set (one row per unit, one column per occasion per measured variable).
LongToWide.Aggregation	How multiple long rows for the same (unit, level) combination are combined into one wide cell.
LongToWide.Result	The wide data set, the unit keys in row order (one list of row-key values per wide row), and a findings-only report.
MissingnessInjector.Effect	One term in the deletion propensity of a target variable: the effect of a driver variable's standardized value, or of its missingness indicator, on the log odds that the target is deleted.
MissingnessInjector.Mechanism	The terms of the deletion mechanism beyond the per-variable level and the row effect.
MissingnessInjector.MechanismClass	The mechanism class of an injection.
MissingnessInjector.MechanismReport	What the mechanism was, and how monotone the realized pattern is.
MissingnessInjector.Report	A report of what was actually injected, for checking that the realized pattern is the intended one.
MissingnessInjector.Result	The injected data together with its reports.
MissingnessInjector.Spec	The injection specification.
NumberObjectDataSet	Wraps a 2D array of Number objects in such a way that mixed data sets can be stored.
SplitCasesSpec	Specifies how a column (continuous or discrete) should be discretized.
TimeSeriesData	Stores time series data as a list of continuous columns.
UnmixSpec	Minimal, UI-friendly spec for the unmixer.
UnmixSpec.ColliderStyle	The ColliderStyle enum represents different styles for handling colliders during graph learning processes.
UnmixSpec.CovarianceMode	The CovarianceMode enum represents different modes for handling covariance calculations during graph learning processes.
UnmixSpec.GraphLearner	The GraphLearner enum represents different algorithms or strategies used for graph learning processes within a system.
UnmixSpec.SupersetScore	The SupersetScore enum represents statistical ranking correlation coefficients that can be used to assess the relationship between two rankings.
Variable	Interface implemented by classes, instantiations of which are capable of serving as variables for columns in a DataSet.
VariableSource	Inteface implemented by classes, instantiations of which are associated with lists of variables.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.data.audit

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.data.missing

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.data.simulation

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataType	The type of the data set--continuous if all continuous variables, discrete if all discrete variables; otherwise, mixed.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.estimate.v1

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.graph

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.hybridcg

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.regression

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DiscreteVariable	Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.
ICovarianceMatrix	Interface for covariance matrices.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search

Class	Description
CorrelationMatrix	Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.blocks

Class	Description
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.cdnod_pag

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.harness

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.harness.tsbi

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.harness.tsc

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.is

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.mimic

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.rlcd

Class	Description
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.score

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
IndependenceFacts	Stores a list of independence facts.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.test

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
IndependenceFacts	Stores a list of independence facts.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.unmix

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.utils

Class	Description
CorrelationMatrix	Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
DiscreteVariable	Represents a discrete variable as a range of integer-valued categories 0, 1, ..., m - 1, where m is the number of categories for the variable.
ICovarianceMatrix	Interface for covariance matrices.
IndependenceFacts	Stores a list of independence facts.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.search.work_in_progress

Class	Description
CorrelationMatrix	Stores a correlation matrix together with variable names and sample size; intended as a representation of a data set.
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
IndependenceFacts	Stores a list of independence facts.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.sem

Class	Description
CovarianceMatrix	Stores a covariance matrix together with variable names and sample size, intended as a representation of a data set.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
ICovarianceMatrix	Interface for covariance matrices.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.
Simulator	Created by jdramsey on 12/22/15.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.simulation

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
VerticalIntDataBox	Stores a 2D array of int data.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.study.missingness

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.study.performance

Class	Description
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.cmu.tetrad.util

Class	Description
DataModel	Interface implemented by classes, instantiations of which can serve as data models in Tetrad.
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.

Classes in edu.cmu.tetrad.data used by edu.pitt.csb.mgm

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.pitt.csb.stability

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.

Classes in edu.cmu.tetrad.data used by edu.pitt.dbmi.algo.bayesian.constraint.search

Class	Description
DataSet	Implements a rectangular data set, in the sense of being a dataset with a fixed number of columns and a fixed number of rows, the length of each column being constant.
Knowledge	Stores information about required and forbidden edges and common causes for use in algorithm.