Package edu.cmu.tetrad.search.test

Class IndTestProbabilistic

java.lang.Object

edu.cmu.tetrad.search.test.IndTestProbabilistic

All Implemented Interfaces:

IndependenceTest

public class IndTestProbabilistic
extends Object
implements IndependenceTest

Uses BCInference by Cooper and Bui to calculate probabilistic conditional independence judgments.

Version:

$Id: $Id

Author:

josephramsey 3/2014

Constructor Summary

Constructors

Constructor	Description
IndTestProbabilistic(DataSet dataSet)	Initializes the test using a discrete data sets.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Node... z)	Checks the independence fact in question and returns and independence result.
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	checkIndependence.
boolean	determines(Set<Node> z, Node y)	Determines whether a given set of nodes, z, determines another node, y.
double	getAlpha()	Returns the alpha parameter for the probabilistic test.
DataModel	getData()	Returns the data model associated with this instance.
Map<IndependenceFact,Double>	getH()	Returns a map from independence facts to their probabilities of independence.
double	getPosterior()	Returns the posterior probability of the last independence test.
Node	getVariable(String name)	Retrieves the Node object that matches the given name from the list of nodes.
List<Node>	getVariables()	Returns the list of variables used in this object.
IndependenceTest	indTestSubset(List<Node> vars)	Returns an Independence test for a sublist of the variables.
boolean	isVerbose()	Returns the verbose flag indicating whether verbose output should be printed.
double	probConstraint(BCInference bci, BCInference.OP op, Node x, Node y, Node[] z, Map<Node,Integer> indices)	Returns the probability of the constraint x op y | z.
void	setAlpha(double alpha)	Sets the alpha parameter for the probabilistic test.
void	setCutoff(double cutoff)	Sets the cutoff for the independence test.
void	setPriorEquivalentSampleSize(double priorEquivalentSampleSize)	Sets the prior equivalent sample size for the independence test.
void	setThreshold(boolean threshold)	Sets whether the independence test should be thresholded (true) or randomized (false).
void	setVerbose(boolean verbose)	Sets the verbose flag indicating whether verbose output should be printed.

Methods inherited from class java.lang.Object

equals, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait

Methods inherited from interface edu.cmu.tetrad.search.IndependenceTest

getCov, getDataSets, getSampleSize, getVariableNames, toString

Constructor Details

IndTestProbabilistic

public IndTestProbabilistic(DataSet dataSet)

Initializes the test using a discrete data sets.

Parameters:

dataSet - a DataSet object

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Returns an Independence test for a sublist 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.

Returns an 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:

an IndependenceResult (see).

See Also:

• IndependenceResult

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 Node... z)

Checks the independence fact in question and returns and independence result.

Returns an 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 Node object

Returns:

The independence result.

See Also:

• IndependenceResult

probConstraint

public double probConstraint(BCInference bci,
 BCInference.OP op,
 Node x,
 Node y,
 Node[] z,
 Map<Node,Integer> indices)

Returns the probability of the constraint x op y | z.

Parameters:

bci - The BCInference object.

op - The operator.

x - The first variable.

y - The second variable.

z - The conditioning set.

indices - A map from nodes to their indices.

Returns:

The probability.

getVariables

public List<Node> getVariables()

Returns the list of variables used in this object.

Specified by:

getVariables in interface IndependenceTest

Returns:

A List of Node objects representing the variables used.

getVariable

public Node getVariable(String name)

Retrieves the Node object that matches the given name from the list of nodes.

Specified by:

getVariable in interface IndependenceTest

Parameters:

name - The name of the variable to retrieve.

Returns:

The Node object matching the given name, or null if no match is found.

determines

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

Determines whether a given set of nodes, z, determines another node, y.

Specified by:

determines in interface IndependenceTest

Parameters:

z - A Set of nodes representing the conditioning set.

y - The node for which determination is checked.

Returns:

true if z determines y, false otherwise.

getAlpha

public double getAlpha()

Returns the alpha parameter for the probabilistic test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

The alpha parameter.

setAlpha

public void setAlpha(double alpha)

Sets the alpha parameter for the probabilistic test.

Specified by:

setAlpha in interface IndependenceTest

Parameters:

alpha - The alpha parameter to set.

getData

public DataModel getData()

Returns the data model associated with this instance.

Specified by:

getData in interface IndependenceTest

Returns:

The data model.

See Also:

• DataSet
• ICovarianceMatrix
• DataModel

getH

public Map<IndependenceFact,Double> getH()

Returns a map from independence facts to their probabilities of independence.

Returns:

The map.

getPosterior

public double getPosterior()

Returns the posterior probability of the last independence test.

Returns:

The posterior probability.

isVerbose

public boolean isVerbose()

Returns the verbose flag indicating whether verbose output should be printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

The verbose flag.

setVerbose

public void setVerbose(boolean verbose)

Sets the verbose flag indicating whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - true if verbose output should be printed, false otherwise.

setThreshold

public void setThreshold(boolean threshold)

Sets whether the independence test should be thresholded (true) or randomized (false).

Parameters:

threshold - true if the independence test should be thresholded, false if it should be randomized.

setCutoff

public void setCutoff(double cutoff)

Sets the cutoff for the independence test.

Parameters:

cutoff - the cutoff for the independence test.

setPriorEquivalentSampleSize

public void setPriorEquivalentSampleSize(double priorEquivalentSampleSize)

Sets the prior equivalent sample size for the independence test. The prior equivalent sample size is a parameter used in the calculation of the test statistic. A higher sample size will make the test more conservative, while a lower sample size will make the test more liberal.

Parameters:

priorEquivalentSampleSize - the prior equivalent sample size to set