Package edu.cmu.tetrad.search.test

Class IndTestMvpLrt

java.lang.Object

edu.cmu.tetrad.search.test.IndTestMvpLrt

All Implemented Interfaces:

IndependenceTest

public class IndTestMvpLrt
extends Object
implements IndependenceTest

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

Andrews, B., Ramsey, J., & Cooper, G. F. (2018). Scoring Bayesian networks of mixed variables. International journal of data science and analytics, 6, 3-18.

Version:

$Id: $Id

Author:

Bryan Andrews

Constructor Summary

Constructors

Constructor	Description
IndTestMvpLrt(DataSet data, double alpha, int fDegree, boolean discretize)	Constructor.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Determines whether two nodes are independent given a set of conditioning nodes.
boolean	determines(List<Node> z, Node y)	Determines whether two nodes are independent given a set of conditioning nodes.
double	getAlpha()	Returns the significance level of the independence test.
DataSet	getData()	Returns the data.
List<Node>	getVariables()	Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.
IndependenceTest	indTestSubset(List<Node> vars)	Returns an Independence test for a sublist of the variables.
boolean	isVerbose()	Returns whether verbose output should be printed.
void	setAlpha(double alpha)	Sets the significance level of the independence test.
void	setVerbose(boolean verbose)	Sets whether this test will print verbose output.

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

checkIndependence, determines, getCov, getDataSets, getSampleSize, getVariable, getVariableNames, toString

Constructor Details

IndTestMvpLrt

public IndTestMvpLrt(DataSet data,
 double alpha,
 int fDegree,
 boolean discretize)

Constructor.

Parameters:

data - The mixed continuous/discrete dataset.

alpha - The significance level.

fDegree - The f degree.

discretize - True if continuous children should be discretized.

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:

The IndependenceTest object for the sublist of variables.

checkIndependence

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

Determines whether two nodes are independent 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 test.

Throws:

RuntimeException - if an undefined p-value is encountered.

See Also:

• IndependenceResult

getVariables

public List<Node> getVariables()

Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.

Specified by:

getVariables in interface IndependenceTest

Returns:

This list.

determines

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

Determines whether two nodes are independent given a set of conditioning nodes.

Parameters:

z - The set of conditioning nodes.

y - The second node.

Returns:

true if the two nodes are independent, false otherwise.

Throws:

UnsupportedOperationException - if the method is not implemented.

getAlpha

public double getAlpha()

Returns the significance level of the independence test.

Specified by:

getAlpha in interface IndependenceTest

Returns:

This level.

Throws:

UnsupportedOperationException - if there is no significance level.

setAlpha

public void setAlpha(double alpha)

Sets the significance level of the independence test.

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

isVerbose

public boolean isVerbose()

Returns whether verbose output should be printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

true if verbose output should be printed, false otherwise

setVerbose

public void setVerbose(boolean verbose)

Sets whether this test will print verbose output.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

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