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., invalid input: '&' Cooper, G. F. (2018). Scoring Bayesian networks of mixed variables. International journal of data science and analytics, 6, 3-18.

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, List<Node> z)	Returns an independence result for x _||_ y | z.
boolean	determines(List<Node> z, Node y)	Returns true if y is determined the variable in z.
double	getAlpha()	Returns the significance level of the independence test.
DataSet	getData()	Returns the data.
double	getPValue()	Returns The probability associated with the most recently executed independence test, of Double.NaN if p value is not meaningful for this test.
double	getScore()	Returns alph - p.
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 searchVariables.
boolean	isVerbose()	Returns true if verbose output is printed.
void	setAlpha(double alpha)	Sets the significance level.
void	setVerbose(boolean verbose)	Returns whether verbose output should be printed.

Methods inherited from class java.lang.Object

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

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

checkIndependence, 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 searchVariables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Returns:

this test.

See Also:

• IndependenceTest

checkIndependence

public IndependenceResult checkIndependence(Node x,
 Node y,
 List<Node> z)

Returns an independence result for x _||_ y | z.

Specified by:

checkIndependence in interface IndependenceTest

Returns:

This result.

See Also:

• IndependenceResult

getPValue

public double getPValue()

Returns The probability associated with the most recently executed independence test, of Double.NaN if p value is not meaningful for this test.

Returns:

This p-value.

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)

Description copied from interface: IndependenceTest

Returns true if y is determined the variable in z.

Specified by:

determines in interface IndependenceTest

Returns:

True if so.

Throws:

javax.help.UnsupportedOperationException - Method 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.

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

getScore

public double getScore()

Returns alph - p.

Specified by:

getScore in interface IndependenceTest

Returns:

This score.

isVerbose

public boolean isVerbose()

Returns true if verbose output is printed.

Specified by:

isVerbose in interface IndependenceTest

Returns:

True if so.

setVerbose

public void setVerbose(boolean verbose)

Returns whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True if so.