Package edu.cmu.tetrad.search.test
Class IndTestTrekSep
java.lang.Object
edu.cmu.tetrad.search.test.IndTestTrekSep
- All Implemented Interfaces:
IndependenceTest
Checks d-separations in structural model using t-separations over indicators.
- Author:
- Adam Brodie
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Constructor Summary
ConstructorsConstructorDescriptionIndTestTrekSep
(ICovarianceMatrix covMatrix, double alpha, List<List<Node>> clustering, List<Node> latents) Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level. -
Method Summary
Modifier and TypeMethodDescriptioncheckIndependence
(Node x, Node y, Set<Node> z) Determines whether variable x is independent of variable y given a list of conditioning variables z.boolean
determines
(List<Node> z, Node x) IfisDeterminismAllowed()
, defers to IndTestFisherZD; otherwise throws UnsupportedOperationException.double
getAlpha()
Gets the model significance level.getCov()
Returns the covariance matrix.getData()
Returns the datasets for this testint
Returns the sample size.getVariable
(String name) Returns the variable with the given name.Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.indTestSubset
(List<Node> vars) Creates a new independence test instance for a sublist of the variables.boolean
Returns true if verbose output should be printed.void
setAlpha
(double alpha) Sets the significance level at which independence judgments should be made.void
setVariables
(List<Node> variables) Sets the varialbe to this list (of the same length).void
setVerbose
(boolean verbose) Sets whether verbose output should be printed.toString()
Returns a string representation of this test.Methods inherited from class java.lang.Object
clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait
Methods inherited from interface edu.cmu.tetrad.search.IndependenceTest
checkIndependence, determines, getVariableNames
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Constructor Details
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IndTestTrekSep
public IndTestTrekSep(ICovarianceMatrix covMatrix, double alpha, List<List<Node>> clustering, List<Node> latents) Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.- Parameters:
covMatrix
- The covariance over the measures.alpha
- The significance level.clustering
- The clustering of the measured variables. In each cluster, all measured variable in the cluster are explained by a single latent.latents
- The list of latent variables for the clusters, in order.
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Method Details
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indTestSubset
Creates a new independence test instance for a sublist of the variables.- Specified by:
indTestSubset
in interfaceIndependenceTest
- Parameters:
vars
- The sublist.
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checkIndependence
Determines whether variable x is independent of variable y given a list of conditioning variables z.- Specified by:
checkIndependence
in interfaceIndependenceTest
- Parameters:
x
- the one variable being compared.y
- the second variable being compared.z
- the list of conditioning variables.- Returns:
- True iff x _||_ y | z.
- Throws:
org.apache.commons.math3.linear.SingularMatrixException
- if a matrix singularity is encountered.- See Also:
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getAlpha
public double getAlpha()Gets the model significance level.- Specified by:
getAlpha
in interfaceIndependenceTest
- Returns:
- This alpha.
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setAlpha
public void setAlpha(double alpha) Sets the significance level at which independence judgments should be made. Affects the cutoff for partial correlations to be considered statistically equal to zero.- Specified by:
setAlpha
in interfaceIndependenceTest
- Parameters:
alpha
- This significance level.
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getVariables
Returns the list of variables over which this independence checker is capable of determinine independence relations-- that is, all the variables in the given graph or the given data set.- Specified by:
getVariables
in interfaceIndependenceTest
- Returns:
- This list.
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setVariables
Sets the varialbe to this list (of the same length). Useful is multiple test are used that need the same object-identical lists of variables.- Parameters:
variables
- This list.
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getVariable
Returns the variable with the given name.- Specified by:
getVariable
in interfaceIndependenceTest
- Returns:
- This variable.
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determines
IfisDeterminismAllowed()
, defers to IndTestFisherZD; otherwise throws UnsupportedOperationException.- Returns:
- True if so
- Throws:
UnsupportedOperationException
- If the above condition is not met.
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getData
- Specified by:
getData
in interfaceIndependenceTest
- Returns:
- The data model for the independence test, either a DataSet or a CovarianceMatrix.
- Throws:
UnsupportedOperationException
- Always.- See Also:
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toString
Returns a string representation of this test.- Specified by:
toString
in interfaceIndependenceTest
- Overrides:
toString
in classObject
- Returns:
- This string.
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getCov
Returns the covariance matrix.- Specified by:
getCov
in interfaceIndependenceTest
- Returns:
- This matrix.
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getDataSets
Description copied from interface:IndependenceTest
Returns the datasets for this test- Specified by:
getDataSets
in interfaceIndependenceTest
- Returns:
- these datasets.
- Throws:
UnsupportedOperationException
- Always.
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getSampleSize
public int getSampleSize()Returns the sample size.- Specified by:
getSampleSize
in interfaceIndependenceTest
- Returns:
- This size.
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isVerbose
public boolean isVerbose()Returns true if verbose output should be printed.- Specified by:
isVerbose
in interfaceIndependenceTest
- Returns:
- True, if so.
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setVerbose
public void setVerbose(boolean verbose) Sets whether verbose output should be printed.- Specified by:
setVerbose
in interfaceIndependenceTest
- Parameters:
verbose
- True, if so.
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