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)	checkIndependence.
boolean	determines(List<Node> z, Node x)
double	getAlpha()	Getter for the field alpha.
DataSet	getData()	getData.
double	getPValue()	getPValue.
List<Node>	getVariables()	Getter for the field variables.
IndependenceTest	indTestSubset(List<Node> vars)	Returns an Independence test for a sublist of the variables.
boolean	isVerbose()	isVerbose.
void	setAlpha(double alpha)	Sets the significance level.
void	setVerbose(boolean verbose)	Sets whether this test will print verbose output.
String	toString()	toString.

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)

Returns an Independence test for a sublist of the variables.

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

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Returns:

a IndependenceTest object

checkIndependence

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

checkIndependence.

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

getPValue

public double getPValue()

getPValue.

Returns:

the probability associated with the most recently computed 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.

Sets the significance level for future tests.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - This level.

getVariables

public List<Node> getVariables()

Getter for the field variables.

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.

determines

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

Throws:

UnsupportedOperationException

getData

public DataSet getData()

getData.

Specified by:

getData in interface IndependenceTest

Returns:

a DataSet object

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

toString

public String toString()

toString.

Specified by:

toString in interface IndependenceTest

Overrides:

toString in class Object

Returns:

a string representation of this test.

isVerbose

public boolean isVerbose()

isVerbose.

Specified by:

isVerbose in interface IndependenceTest

Returns:

a boolean

setVerbose

public void setVerbose(boolean verbose)

Sets whether this test will print verbose output.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.