Package edu.cmu.tetrad.search.score

Class EbicScore

java.lang.Object

edu.cmu.tetrad.search.score.EbicScore

All Implemented Interfaces:

Score

public class EbicScore
extends Object
implements Score

Implements the extended BIC (EBIC) score. The reference is here:

Chen, J., & Chen, Z. (2008). Extended Bayesian information criteria for model selection with large model spaces. Biometrika, 95(3), 759-771.

As for all scores in Tetrad, higher scores mean more dependence, and negative scores indicate independence.

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
EbicScore(DataSet dataSet, boolean precomputeCovariances)	Constructs the score using a covariance matrix.
EbicScore(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.

Method Summary

Modifier and Type	Method	Description
boolean	determines(List<Node> z, Node y)	Return a judgment of whether the variable in z determine y exactly.
int	getMaxDegree()	Returns an estimate of max degree of the graph for some algorithms.
int	getSampleSize()	Returns the sample size.
List<Node>	getVariables()	Returns the variables for this score.
boolean	isEffectEdge(double bump)	Returns a judgement for FGES of whether the given bump implies an effect edge.
double	localScore(int i, int... parents)	Returns the score of the node i given its parents.
double	localScoreDiff(int x, int y, int[] z)	Returns the score difference of the graph.
void	setGamma(double gamma)	Sets the gamma parameter for EBIC.

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.score.Score

append, getVariable, localScore, localScore, localScoreDiff, toString

Constructor Details

EbicScore

public EbicScore(ICovarianceMatrix covariances)

Constructs the score using a covariance matrix.

EbicScore

public EbicScore(DataSet dataSet,
 boolean precomputeCovariances)

Constructs the score using a covariance matrix.

Parameters:

dataSet - The continuous dataset to analyze.

precomputeCovariances - Whether the covariances should be precomputed or computed on the fly. True if precomputed.

Method Details

localScoreDiff

public double localScoreDiff(int x,
 int y,
 int[] z)

Description copied from interface: Score

Returns the score difference of the graph.

Specified by:

localScoreDiff in interface Score

Parameters:

x - A node.

y - TAhe node.

z - A set of nodes.

Returns:

localScore(y | z, x) - localScore(y | z).

localScore

public double localScore(int i,
 int... parents)
                  throws RuntimeException

Returns the score of the node i given its parents.

Specified by:

localScore in interface Score

Parameters:

i - The index of the node.

parents - The indices of the node's parents.

Returns:

The score, or NaN if the score cannot be calculated.

Throws:

RuntimeException

getSampleSize

public int getSampleSize()

Returns the sample size.

Specified by:

getSampleSize in interface Score

Returns:

This size.

isEffectEdge

public boolean isEffectEdge(double bump)

Returns a judgement for FGES of whether the given bump implies an effect edge.

Specified by:

isEffectEdge in interface Score

Parameters:

bump - The bump

Returns:

True if so

See Also:

• Fges

getVariables

public List<Node> getVariables()

Returns the variables for this score.

Specified by:

getVariables in interface Score

Returns:

Thsi list.

getMaxDegree

public int getMaxDegree()

Returns an estimate of max degree of the graph for some algorithms.

Specified by:

getMaxDegree in interface Score

Returns:

This max degree.

See Also:

• Fges
• MagSemBicScore

determines

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

Return a judgment of whether the variable in z determine y exactly.

Specified by:

determines in interface Score

Parameters:

z - The set of nodes.

y - The node.

Returns:

This judgment

setGamma

public void setGamma(double gamma)

Sets the gamma parameter for EBIC.

Parameters:

gamma - The gamma parameter.