Package edu.cmu.tetrad.search.work_in_progress

Class IndTestCramerT

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.IndTestCramerT

All Implemented Interfaces:

IndependenceTest

public final class IndTestCramerT
extends Object
implements IndependenceTest

Checks conditional independence for continuous variables using Cramer's T-test formula (Cramer, Mathematical Methods of Statistics (1951), page 413).

Version:

$Id: $Id

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
IndTestCramerT(CorrelationMatrix covMatrix, double alpha)	Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.
IndTestCramerT(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).
IndTestCramerT(ICovarianceMatrix covMatrix, double alpha)	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 Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Checks the independence between two nodes given a set of conditioning nodes.
boolean	determines(List<Node> z, Node x)	Determines whether the given variables are conditionally independent.
double	getAlpha()	Getter for the field alpha.
DataSet	getData()	Retrieves the dataset used in the independence test.
double	getPValue()	Calculates the p-value for the independence test.
List<Node>	getVariables()	Retrieves the list of variables used in the independence test.
IndependenceTest	indTestSubset(List<Node> vars)	This method performs an independence test based on a given sublist of variables.
boolean	isVerbose()	Determines if verbose output is enabled or disabled.
void	setAlpha(double alpha)	Sets the significance level for the independence test.
void	setVerbose(boolean verbose)	Sets the verbose flag to determine if verbose output should be enabled or disabled.
String	toString()	Returns a string representation of the object.

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, determines, getCov, getDataSets, getSampleSize, getVariable, getVariableNames

Constructor Details

IndTestCramerT

public IndTestCramerT(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 with all continuous columns.

alpha - the alpha level of the test.

IndTestCramerT

public IndTestCramerT(CorrelationMatrix covMatrix,
 double alpha)

Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.

Parameters:

covMatrix - a CorrelationMatrix object

alpha - a double

IndTestCramerT

public IndTestCramerT(ICovarianceMatrix covMatrix,
 double alpha)

Constructs a new independence test that will determine conditional independence facts using the given correlation matrix and the given significance level.

Parameters:

covMatrix - a ICovarianceMatrix object

alpha - a double

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

This method performs an independence test based on a given sublist of variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables to perform the independence test on.

Returns:

An IndependenceTest object representing the results of the test.

Throws:

IllegalArgumentException - If the sublist of variables is empty or contains variables that are not original variables.

checkIndependence

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

Checks the independence between two nodes given a set of conditioning nodes.

Specified by:

checkIndependence in interface IndependenceTest

Parameters:

x - The first node.

y - The second node.

_z - The set of conditioning nodes.

Returns:

The result of the independence check.

Throws:

NullPointerException - If _z is null or contains null elements.

IllegalArgumentException - If the submatrix contains missing values.

RuntimeException - If the submatrix is singular or the p-value is undefined.

See Also:

• IndependenceResult

getPValue

public double getPValue()

Calculates the p-value for the independence test. The p-value is calculated by integrating the probability density function (pdf) over the range of storedR (absolute value) to 1.0 with 100 intervals, and then multiplying the result by 2.0.

Returns:

the p-value for the independence test.

getAlpha

public double getAlpha()

Getter for the field alpha.

Specified by:

getAlpha in interface IndependenceTest

Returns:

the getModel significance level.

setAlpha

public void setAlpha(double alpha)

Sets the significance level for the independence test.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - The significance level, must be between 0.0 and 1.0 (inclusive).

Throws:

IllegalArgumentException - If the significance level is out of range.

getVariables

public List<Node> getVariables()

Retrieves the list of variables used in the independence test.

Specified by:

getVariables in interface IndependenceTest

Returns:

A list of Node objects representing the variables used in the test.

determines

public boolean determines(List<Node> z,
 Node x)
                   throws UnsupportedOperationException

Determines whether the given variables are conditionally independent.

Parameters:

z - The set of conditioning nodes.

x - The target node.

Returns:

true if the variables are conditionally independent, false otherwise.

Throws:

UnsupportedOperationException - If a matrix operation fails.

getData

public DataSet getData()

Retrieves the dataset used in the independence test.

Specified by:

getData in interface IndependenceTest

Returns:

The dataset used in the independence test.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

toString

public String toString()

Returns a string representation of the object.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

A string representation of the object.

isVerbose

public boolean isVerbose()

Determines if verbose output is enabled or disabled.

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 determine if verbose output should be enabled or disabled.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True if the verbose output should be enabled, false otherwise.