Package edu.cmu.tetrad.search.test

Class IndTestGSquare

java.lang.Object

edu.cmu.tetrad.search.test.IndTestGSquare

All Implemented Interfaces:

IndependenceTest

public final class IndTestGSquare
extends Object
implements IndependenceTest

Checks the conditional independence X _||_ Y | S, where S is a set of discrete variable, and X and Y are discrete variable not in S, by applying a conditional G Square test. A description of such a test is given in Fienberg, "The Analysis of Cross-Classified Categorical Data," 2nd edition. The formula for degrees of freedom used in this test are equivalent to the formulation on page 142 of Fienberg.

Author:

josephramsey

See Also:

• GSquareTest

Constructor Summary

Constructors

Constructor	Description
IndTestGSquare(DataSet dataSet, double alpha)	Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Determines whether variable x is independent of variable y given a list of conditioning varNames z.
boolean	determines(Set<Node> _z, Node x)	Returns a judgment whether the variables in z determine x.
double	getAlpha()	Gets the getModel significance level.
DataSet	getData()	Returns the data.
double	getPValue()	Returns the p value associated with the most recent call of isIndependent.
List<Node>	getVariables()	Return 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.
IndependenceTest	indTestSubset(List<Node> vars)	Creates a new IndTestGSquare for a sublist of the variables.
boolean	isVerbose()	Returns True if verbose output is printed.
void	setAlpha(double alpha)	Sets the significance level at which independence judgments should be made.
void	setDeterminationP(double determinationP)	Sets the threshold for making judgments of detemrination.
void	setVerbose(boolean verbose)	Sets whether verbose output is 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, getCov, getDataSets, getSampleSize, getVariable, getVariableNames

Constructor Details

IndTestGSquare

public IndTestGSquare(DataSet dataSet,
 double alpha)

Constructs a new independence checker to check conditional independence facts for discrete data using a g square test.

Parameters:

dataSet - the discrete data set.

alpha - the significance level of the tests.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Creates a new IndTestGSquare for a sublist of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - This sublist.

getPValue

public double getPValue()

Returns the p value associated with the most recent call of isIndependent.

Returns:

This p-value.

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 Set<Node> _z)

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

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

x - the one variable being compared.

y - the second variable being compared.

_z - the list of conditioning varNames.

Returns:

True iff x _||_ y | z.

See Also:

• IndependenceResult

getAlpha

public double getAlpha()

Gets the getModel significance level.

Specified by:

getAlpha in interface IndependenceTest

Returns:

this number.

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 - the new significance level.

getVariables

public List<Node> getVariables()

Return 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 interface IndependenceTest

Returns:

This list.

toString

public String toString()

Returns a String representation of this test.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

This string.

determines

public boolean determines(Set<Node> _z,
 Node x)

Returns a judgment whether the variables in z determine x.

Specified by:

determines in interface IndependenceTest

Parameters:

_z - The list of variables z1,...,zn with respect to which we want to know whether z determines x oir z.

x - The one variable whose determination by z we want to know.

Returns:

true if it is estimated that z determines x or z determines y.

setDeterminationP

public void setDeterminationP(double determinationP)

Sets the threshold for making judgments of detemrination.

Parameters:

determinationP - This threshold.

getData

public DataSet getData()

Returns the data.

Specified by:

getData in interface IndependenceTest

Returns:

This data.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

isVerbose

public boolean isVerbose()

Returns True if verbose output is printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

True, if so.

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output is printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.