Package edu.cmu.tetrad.search

Class IndTestCodec

java.lang.Object

edu.cmu.tetrad.search.IndTestCodec

All Implemented Interfaces:

IndependenceTest

public final class IndTestCodec
extends Object
implements IndependenceTest

Checks conditional independence of variable in a continuous data set using Fisher's Z test. See Spirtes, Glymour, and Scheines, "Causation, Prediction and Search," 2nd edition, page 94.

Author:

Joseph Ramsey, Frank Wimberly adapted IndTestCramerT for Fisher's Z

Constructor Summary

Constructors

Constructor	Description
IndTestCodec(DataSet dataSet, double alpha)	Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous).

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node y, Node z, List<Node> x)	Determines whether variable x is independent of variable y given a list of conditioning variables z.
boolean	determines(List<Node> z, Node y)
double	getAlpha()
ICovarianceMatrix	getCov()
List<Matrix>	getCovMatrices()
DataModel	getData()
List<DataSet>	getDataSets()
int	getSampleSize()
double	getScore()	A score that is higher with more likely models.
Node	getVariable(String name)
List<String>	getVariableNames()
List<Node>	getVariables()
IndependenceTest	indTestSubset(List<Node> vars)	Creates a new independence test instance for a subset of the variables.
boolean	isVerbose()
void	setAlpha(double alpha)	Sets the significance level.
void	setVerbose(boolean verbose)
String	toString()

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

Constructor Details

IndTestCodec

public IndTestCodec(DataSet dataSet,
 double alpha)

Constructs a new Independence test which checks independence facts based on the correlation matrix implied by the given data set (must be continuous). The given significance level is used.

Parameters:

dataSet - A data set containing only continuous columns.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Creates a new independence test instance for a subset of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Returns:

an Independence test for a subset of the variables.

checkIndependence

public IndependenceResult checkIndependence(Node y,
 Node z,
 List<Node> x)

Determines whether variable x is independent of variable y given a list of conditioning variables z.

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

y - the second variable being compared.

z - the list of conditioning variables.

x - the one variable being compared.

Returns:

true iff x _||_ y | z.

Throws:

RuntimeException - if a matrix singularity is encountered.

getVariables

public List<Node> getVariables()

Specified by:

getVariables in interface IndependenceTest

Returns:

the list of variables over which this independence checker is capable of determinining independence relations.

getVariable

public Node getVariable(String name)

Specified by:

getVariable in interface IndependenceTest

Returns:

the variable by the given name.

getVariableNames

public List<String> getVariableNames()

Specified by:

getVariableNames in interface IndependenceTest

Returns:

the list of names for the variables in getNodesInEvidence.

determines

public boolean determines(List<Node> z,
 Node y)

Specified by:

determines in interface IndependenceTest

Returns:

true if y is determined the variable in z.

getAlpha

public double getAlpha()

Specified by:

getAlpha in interface IndependenceTest

Returns:

the significance level of the independence test.

setAlpha

public void setAlpha(double alpha)

Description copied from interface: IndependenceTest

Sets the significance level.

Specified by:

setAlpha in interface IndependenceTest

getData

public DataModel getData()

Specified by:

getData in interface IndependenceTest

Returns:

The data model for the independence test.

getCov

public ICovarianceMatrix getCov()

Specified by:

getCov in interface IndependenceTest

getDataSets

public List<DataSet> getDataSets()

Specified by:

getDataSets in interface IndependenceTest

getSampleSize

public int getSampleSize()

Specified by:

getSampleSize in interface IndependenceTest

getCovMatrices

public List<Matrix> getCovMatrices()

Specified by:

getCovMatrices in interface IndependenceTest

getScore

public double getScore()

Description copied from interface: IndependenceTest

A score that is higher with more likely models.

Specified by:

getScore in interface IndependenceTest

setVerbose

public void setVerbose(boolean verbose)

Specified by:

setVerbose in interface IndependenceTest

isVerbose

public boolean isVerbose()

Specified by:

isVerbose in interface IndependenceTest

toString

public String toString()

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object