Package edu.cmu.tetrad.search.test

Class IndTestDegenerateGaussianLrt

java.lang.Object

edu.cmu.tetrad.search.test.IndTestDegenerateGaussianLrt

All Implemented Interfaces:

IndependenceTest

public class IndTestDegenerateGaussianLrt
extends Object
implements IndependenceTest

Implements a degenerate Gaussian score as a LRT. The reference is here:

Andrews, B., Ramsey, J., & Cooper, G. F. (2019, July). Learning high-dimensional directed acyclic graphs with mixed data-types. In The 2019 ACM SIGKDD Workshop on Causal Discovery (pp. 4-21). PMLR.

Version:

$Id: $Id

Author:

Bryan Andrews

Nested Class Summary

Nested Classes

Modifier and Type	Class	Description
static class	IndTestDegenerateGaussianLrt.Ret	Stores a return value for a likelihood--i.e., a likelihood value and the degrees of freedom for it.

Constructor Summary

Constructors

Constructor	Description
IndTestDegenerateGaussianLrt(DataSet dataSet)	Constructs the score using a covariance matrix.

Method Summary

Modifier and Type	Method	Description
IndependenceResult	checkIndependence(Node x, Node y, Set<Node> _z)	Returns an independence result specifying whether x _||_ y | Z and what its p-values are.
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 dataset being analyzed.
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.
List<Node>	getVariables()	Returns the list of searchVariables over which this independence checker is capable of determinining independence relations.
IndependenceTest	indTestSubset(List<Node> vars)	Subsets the variables used in the independence test.
boolean	isVerbose()	Returns true iff verbose output should be printed.
void	setAlpha(double alpha)	Sets the significance level.
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

IndTestDegenerateGaussianLrt

public IndTestDegenerateGaussianLrt(DataSet dataSet)

Constructs the score using a covariance matrix.

Parameters:

dataSet - The data being analyzed.

Method Details

indTestSubset

public IndependenceTest indTestSubset(List<Node> vars)

Subsets the variables used in the independence test.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Returns:

The IndependenceTest object with subset of variables.

checkIndependence

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

Returns an independence result specifying whether x _||_ y | Z and what its p-values are.

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()

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)

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

Parameters:

z - The list of nodes z.

y - The node y.

Returns:

True if the list of nodes z determines y, false otherwise.

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 dataset being analyzed.

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.