Package edu.cmu.tetrad.search.work_in_progress

Class IndTestFisherZGeneralizedInverse

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.IndTestFisherZGeneralizedInverse

All Implemented Interfaces:

IndependenceTest

public final class IndTestFisherZGeneralizedInverse
extends Object
implements IndependenceTest

Checks independence of X _||_ Y | Z for variables X and Y and list Z of variables. Partial correlations are calculated using generalized inverses, so linearly dependent variables do not throw exceptions. Must supply a continuous data set; don't know how to do this with covariance or correlation matrices.

Author:

josephramsey, Frank Wimberly adapted IndTestCramerT for Fisher's Z

Constructor Summary

Constructors

Constructor	Description
IndTestFisherZGeneralizedInverse(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 xVar, Node yVar, Set<Node> _z)	Determines whether variable x is independent of variable y given a list of conditioning variables z.
boolean	determines(List<Node> zList, Node xVar)	Returns true just in case the varialbe in zList determine xVar.
double	getAlpha()	Gets the getModel significance level.
DataSet	getData()	Returns the data being analyzed.
double	getPValue()
List<Node>	getVariables()
IndependenceTest	indTestSubset(List<Node> vars)	Creates a new IndTestCramerT instance for a subset of the variables.
boolean	isVerbose()	Returns True just in case verbose output should be printed.
void	setAlpha(double alpha)	Sets the significance level at which independence judgments should be made.
void	setVerbose(boolean verbose)	Sets whether verbose output should be printed.
String	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, getCov, getDataSets, getSampleSize, getVariable, getVariableNames

Constructor Details

IndTestFisherZGeneralizedInverse

public IndTestFisherZGeneralizedInverse(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.

alpha - The alpha level of the test.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Creates a new IndTestCramerT instance for a subset of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

checkIndependence

public IndependenceResult checkIndependence(Node xVar,
 Node yVar,
 Set<Node> _z)

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

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

xVar - the one variable being compared.

yVar - the second variable being compared.

_z - the list of conditioning variables.

Returns:

True iff x _||_ y | z.

Throws:

RuntimeException - if a matrix singularity is encountered.

See Also:

• IndependenceResult

getPValue

public double getPValue()

Returns:

the probability associated with the most recently computed independence test.

getAlpha

public double getAlpha()

Gets the getModel significance level.

Specified by:

getAlpha in interface IndependenceTest

Returns:

This level.

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 interface IndependenceTest

Parameters:

alpha - This level.

getVariables

public List<Node> getVariables()

Specified by:

getVariables in interface IndependenceTest

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.

toString

public String toString()

Description copied from interface: IndependenceTest

Returns a string representation of this test.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

the variable with the given name.

getData

public DataSet getData()

Returns the data being analyzed.

Specified by:

getData in interface IndependenceTest

Returns:

This data.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

isVerbose

public boolean isVerbose()

Returns True just in case verbose output should be printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

This.

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.

determines

public boolean determines(List<Node> zList,
 Node xVar)

Returns true just in case the varialbe in zList determine xVar.

Returns:

True, if so.