Package edu.cmu.tetrad.search.test

Class IndTestGSquare

java.lang.Object

edu.cmu.tetrad.search.test.IndTestGSquare

All Implemented Interfaces:

EffectiveSampleSizeSettable, IndependenceTest, RowsSettable

public final class IndTestGSquare
extends Object
implements IndependenceTest, EffectiveSampleSizeSettable, RowsSettable

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 is equivalent to the formulation on page 142 of Fienberg.

Version:

$Id: $Id

Author:

josephramsey

See Also:

• ChiSquareTest

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)	Determines whether variable x is independent of a set of variables _z.
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<Integer>	getRows()	Retrieves the list of rows to use for the test.
List<Node>	getVariables()	Return the list of variables over which this independence checker is capable of determining independence relations-- that is, all the variables in the given graph or the given data set.
IndependenceTest	indTestSubset(List<Node> vars)	Performs an independence test on a subset of variables.
boolean	isVerbose()	Returns whether verbose output is enabled or not.
void	setAlpha(double alpha)	Sets the significance level at which independence judgments should be made.
void	setCellTableType(ChiSquareTest.CellTableType cellTableType)	Sets the cell table type.
void	setDeterminationP(double determinationP)	Sets the threshold for making judgments of determination.
void	setEffectiveSampleSize(int sampleSize)	Sets the sample size if the sample size of the data or covariance matrix is not the sample size that the test should use.
void	setMinCountPerCell(double minCountPerCell)	The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom.
void	setRows(List<Integer> rows)	Sets the list of rows to use for the test.
void	setVerbose(boolean verbose)	Sets the verbose flag to enable or disable verbose output.
String	toString()	Returns a String representation of this test.

Methods inherited from class java.lang.Object

equals, 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)

Performs an independence test on a subset of variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - the subset of variables to perform the test on

Returns:

the result of the independence test for the subset of variables

Throws:

IllegalArgumentException - if the subset of variables is empty

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 - a Node object

y - a Node object

_z - a Set object

Returns:

a IndependenceResult object

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 - This level.

getVariables

public List<Node> getVariables()

Return the list of variables over which this independence checker is capable of determining 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)

Determines whether variable x is independent of a set of variables _z.

Specified by:

determines in interface IndependenceTest

Parameters:

_z - a set of variables to condition on

x - the variable to check for independence

Returns:

true if variable x is independent of _z, false otherwise

Throws:

NullPointerException - if _z or any element in _z is null

IllegalArgumentException - if any variable in _z or x was not used in the constructor

setDeterminationP

public void setDeterminationP(double determinationP)

Sets the threshold for making judgments of determination.

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 whether verbose output is enabled or not.

Specified by:

isVerbose in interface IndependenceTest

Returns:

true if verbose output is enabled, false otherwise

setVerbose

public void setVerbose(boolean verbose)

Sets the verbose flag to enable or disable verbose output.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - true to enable verbose output, false to disable it.

setMinCountPerCell

public void setMinCountPerCell(double minCountPerCell)

The minimum number of counts per conditional table for chi-square for that table and its degrees of freedom to be included in the overall chi-square and degrees of freedom. Note that this should not be too small, or the chi-square distribution will not be a good approximation to the distribution of the test statistic.

Parameters:

minCountPerCell - The minimum number of counts per conditional table. The default is 1; this must be >= 0.

getRows

public List<Integer> getRows()

Retrieves the list of rows to use for the test.

Specified by:

getRows in interface RowsSettable

Returns:

The list of rows to use for the test.

setRows

public void setRows(List<Integer> rows)

Sets the list of rows to use for the test.

Specified by:

setRows in interface RowsSettable

Parameters:

rows - The list of rows to use for the test.

Throws:

IllegalArgumentException - if any of the rows are out of bounds

setEffectiveSampleSize

public void setEffectiveSampleSize(int sampleSize)

Sets the sample size if the sample size of the data or covariance matrix is not the sample size that the test should use.

Specified by:

setEffectiveSampleSize in interface EffectiveSampleSizeSettable

Parameters:

sampleSize - The sample size to use.

setCellTableType

public void setCellTableType(ChiSquareTest.CellTableType cellTableType)

Sets the cell table type.

Parameters:

cellTableType - The cell table type.