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., invalid input: '&' 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.

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, List<Node> z)	Returns an independence result specifying whether x _||_ y | Z and what its p-value are.
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 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 tis test.
double	getScore()	Returns a value that more positive for stronger dependence and positive only if dependence holds.
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 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

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

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

checkIndependence, 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)

Description copied from interface: IndependenceTest

Returns an Independence test for a sublist of the variables.

Specified by:

indTestSubset in interface IndependenceTest

Parameters:

vars - The sublist of variables.

Throws:

UnsupportedOperationException - This method is not implemented.

checkIndependence

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

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

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 tis 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)

Returns true if y is determined the variable in z.

Specified by:

determines in interface IndependenceTest

Returns:

True if so.

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

getScore

public double getScore()

Returns a value that more positive for stronger dependence and positive only if dependence holds.

Specified by:

getScore in interface IndependenceTest

Returns:

This value.

See Also:

• Fges

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 so.

setVerbose

public void setVerbose(boolean verbose)

Sets whether verbose output should be printed.

Specified by:

setVerbose in interface IndependenceTest

Parameters:

verbose - True if so.