Package edu.cmu.tetrad.search.test
Class IndTestBasisFunctionLrt
java.lang.Object
edu.cmu.tetrad.search.test.IndTestBasisFunctionLrt
- All Implemented Interfaces:
RawMarginalIndependenceTest,IndependenceTest
@Deprecated(since="7.9",
forRemoval=false)
public class IndTestBasisFunctionLrt
extends Object
implements IndependenceTest, RawMarginalIndependenceTest
Deprecated.
The IndTestBasisFunctionLrtCovariance class implements the IndependenceTest interface and provides functionality to
perform conditional independence tests using basis functions and likelihood ratio tests based on residual variances
and covariance matrices. It handles the transformations, embeddings, and statistical computations required to compute
p-values for testing conditional independence of variables.
This class is designed to work with a given dataset, perform embedding transformations based on specified basis function parameters, and efficiently compute the required statistics for hypothesis testing over sets of variables.
Note that compared to the full sample version of this class (see), this class uses a covariance matrix as a sufficient statistic and thus cannot do random row subsetting per test.
- Author:
- josephramsey, bryanandrews
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Constructor Summary
ConstructorsConstructorDescriptionIndTestBasisFunctionLrt(DataSet dataSet, int truncationLimit, double lambda) Deprecated.Constructs an instance of IndTestBasisFunctionLrtCovariance. -
Method Summary
Modifier and TypeMethodDescriptioncheckIndependence(Node x, Node y, Set<Node> z) Deprecated.Tests for the conditional independence of two nodes given a set of conditioning nodes.doublecomputePValue(double[] x, double[] y) Deprecated.Computes the p-value for the statistical test of marginal independence between the two given variables represented by the input arrays.doublegetAlpha()Deprecated.Retrieves the significance level (alpha) for the statistical tests performed by this instance.getData()Deprecated.Retrieves the data model associated with this instance.Deprecated.Retrieves the list of nodes (variables) associated with this instance.booleanDeprecated.Indicates whether verbose mode is enabled.voidsetAlpha(double alpha) Deprecated.Sets the significance level.voidsetDoOneEquationOnly(boolean doOneEquationOnly) Deprecated.When calculation the score for X = <X1 = X, X2, X3,..., Xp> use the equation for X1 only, if true; otherwise, use equations for all of X1, X2,...,Xp.voidsetVerbose(boolean verbose) Deprecated.Enables or disables verbose output.Methods inherited from class java.lang.Object
equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, waitMethods inherited from interface edu.cmu.tetrad.search.test.IndependenceTest
checkIndependence, determines, getCov, getDataSets, getSampleSize, getVariable, getVariableNames, indTestSubset, toStringMethods inherited from interface edu.cmu.tetrad.search.RawMarginalIndependenceTest
computePValue
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Constructor Details
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IndTestBasisFunctionLrt
Deprecated.Constructs an instance of IndTestBasisFunctionLrtCovariance. This constructor initializes the object using a dataset and parameters related to truncation limit, basis type, and basis scale. It processes the input data into an embedded format, computes its covariance matrix, and sets up internal variables for further use.- Parameters:
dataSet- the input dataset containing the variables and data rows to be analyzed.truncationLimit- the limit to truncate the embeddings or basis functions in the data.lambda- Singularity lambda
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Method Details
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computePValue
public double computePValue(double[] x, double[] y) Deprecated.Description copied from interface:RawMarginalIndependenceTestComputes the p-value for the statistical test of marginal independence between the two given variables represented by the input arrays.- Specified by:
computePValuein interfaceRawMarginalIndependenceTest- Parameters:
x- the first variable, represented as an array of doublesy- the second variable, represented as an array of doubles- Returns:
- the computed p-value for the test of marginal independence
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checkIndependence
Deprecated.Tests for the conditional independence of two nodes given a set of conditioning nodes.- Specified by:
checkIndependencein interfaceIndependenceTest- Parameters:
x- The first variable to test, represented as a Node object.y- The second variable to test, represented as a Node object.z- The set of conditioning variables, represented as a Set of Node objects.- Returns:
- An IndependenceResult object representing the outcome of the independence test.
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getVariables
Deprecated.Retrieves the list of nodes (variables) associated with this instance.- Specified by:
getVariablesin interfaceIndependenceTest- Returns:
- a list of Node objects representing the variables.
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getData
Deprecated.Retrieves the data model associated with this instance.- Specified by:
getDatain interfaceIndependenceTest- Returns:
- the current DataModel instance held by this class.
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isVerbose
public boolean isVerbose()Deprecated.Indicates whether verbose mode is enabled. Verbose mode, when enabled, typically results in detailed logging or diagnostic information being output.- Specified by:
isVerbosein interfaceIndependenceTest- Returns:
- true if verbose mode is enabled; false otherwise.
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setVerbose
public void setVerbose(boolean verbose) Deprecated.Enables or disables verbose output.- Specified by:
setVerbosein interfaceIndependenceTest- Parameters:
verbose- True, if so.
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getAlpha
public double getAlpha()Deprecated.Retrieves the significance level (alpha) for the statistical tests performed by this instance.- Specified by:
getAlphain interfaceIndependenceTest- Returns:
- the current significance level as a double.
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setAlpha
public void setAlpha(double alpha) Deprecated.Sets the significance level.- Specified by:
setAlphain interfaceIndependenceTest- Parameters:
alpha- This level.
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setDoOneEquationOnly
public void setDoOneEquationOnly(boolean doOneEquationOnly) Deprecated.When calculation the score for X = <X1 = X, X2, X3,..., Xp> use the equation for X1 only, if true; otherwise, use equations for all of X1, X2,...,Xp.- Parameters:
doOneEquationOnly- True if only the equation for X1 is to be used for X = X1,...,Xp.
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