Package edu.cmu.tetrad.search.test

Class IndTestConditionalGaussianLrt

java.lang.Object

edu.cmu.tetrad.search.test.IndTestConditionalGaussianLrt

All Implemented Interfaces:

IndependenceTest

public class IndTestConditionalGaussianLrt
extends Object
implements IndependenceTest

Performs a test of conditional independence X _||_ Y | Z1...Zn where all searchVariables are either continuous or discrete. This test is valid for both ordinal and non-ordinal discrete searchVariables.

Assumes a conditional Gaussian model and uses a likelihood ratio test.

Version:

$Id: $Id

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
IndTestConditionalGaussianLrt(DataSet data, double alpha, boolean discretize)	Constructor.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Returns and independence result that states whether x _||_y | z and what the p-value of the test is.
boolean	determines(List<Node> z, Node y)	Determines whether a given list of nodes (z) determines a node (y).
double	getAlpha()	Returns the significance level of the independence test.
DataSet	getData()	Returns the data.
List<Node>	getVariables()	Returns the list of variables over which this independence checker is capable of determining independence relations.
IndependenceTest	indTestSubset(List<Node> vars)	This method returns an instance of the IndependenceTest interface that can test the independence of a subset of variables.
boolean	isVerbose()	Returns true iff verbose output should be printed.
void	setAlpha(double alpha)	Sets the significance level.
void	setNumCategoriesToDiscretize(int numCategoriesToDiscretize)	Sets the number of categories used to discretize variables.
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

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

IndTestConditionalGaussianLrt

public IndTestConditionalGaussianLrt(DataSet data,
 double alpha,
 boolean discretize)

Constructor.

Parameters:

data - The data to analyze.

alpha - The significance level.

discretize - Whether discrete children of continuous parents should be discretized.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

This method returns an instance of the IndependenceTest interface that can test the independence of a subset of variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables to test for independence.

Returns:

An instance of the IndependenceTest interface.

See Also:

• IndependenceTest

checkIndependence

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

Returns and independence result that states whether x _||_y | z and what the p-value of the test is.

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

getVariables

public List<Node> getVariables()

Returns the list of variables over which this independence checker is capable of determining independence relations.

Specified by:

getVariables in interface IndependenceTest

Returns:

This list.

determines

public boolean determines(List<Node> z,
 Node y)

Determines whether a given list of nodes (z) determines a node (y).

Parameters:

z - The list of nodes to check if they determine y.

y - The node to check if it is determined by z.

Returns:

True if z determines y, false otherwise.

Throws:

UnsupportedOperationException - if not implemented.

getAlpha

public double getAlpha()

Returns the significance level of the independence test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

This level.

setAlpha

public void setAlpha(double alpha)

Sets the significance level.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - This level.

getData

public DataSet getData()

Returns the data.

Specified by:

getData in interface IndependenceTest

Returns:

This data.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

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.

isVerbose

public boolean isVerbose()

Returns true iff verbose output should be printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

True if the case.

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True, if so.

setNumCategoriesToDiscretize

public void setNumCategoriesToDiscretize(int numCategoriesToDiscretize)

Sets the number of categories used to discretize variables.

Parameters:

numCategoriesToDiscretize - This number, by default 3.