Package edu.cmu.tetrad.search.work_in_progress

Class SemBicScoreDeterministic

java.lang.Object

edu.cmu.tetrad.search.work_in_progress.SemBicScoreDeterministic

All Implemented Interfaces:

Score

public class SemBicScoreDeterministic
extends Object
implements Score

Implements the continuous BIC score for FGES.

Version:

$Id: $Id

Author:

josephramsey

Constructor Summary

Constructors

Constructor	Description
SemBicScoreDeterministic(ICovarianceMatrix covariances)	Constructs the score using a covariance matrix.

Method Summary

Modifier and Type	Method	Description
boolean	determines(List<Node> z, Node y)	Returns true iff the score determines the edge between x and y.
ICovarianceMatrix	getCovariances()	Getter for the field covariances.
DataSet	getDataSet()	getDataSet.
double	getDeterminismThreshold()	Getter for the field determinismThreshold.
int	getMaxDegree()	Returns the max degree, by default 1000.
double	getPenaltyDiscount()	Specialized scoring method for a single parent.
int	getSampleSize()	Getter for the field sampleSize.
List<Node>	getVariables()	The variables of the score.
boolean	isEffectEdge(double bump)	Returns true iff the edge between x and y is an effect edge.
boolean	isVerbose()	isVerbose.
double	localScore(int i, int... parents)	Calculates the sample likelihood and BIC score for i given its parents in a simple SEM model
double	localScoreDiff(int x, int y, int[] z)	Returns the score difference of the graph.
void	setDeterminismThreshold(double determinismThreshold)	Setter for the field determinismThreshold.
void	setPenaltyDiscount(double penaltyDiscount)	Setter for the field penaltyDiscount.
void	setVariables(List<Node> variables)	Setter for the field variables.
void	setVerbose(boolean verbose)	Setter for the field verbose.

Methods inherited from class java.lang.Object

equals, 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

SemBicScoreDeterministic

public SemBicScoreDeterministic(ICovarianceMatrix covariances)

Constructs the score using a covariance matrix.

Parameters:

covariances - a ICovarianceMatrix object

Method Details

localScore

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

Calculates the sample likelihood and BIC score for i given its parents in a simple SEM model

Specified by:

localScore in interface Score

Parameters:

i - a int

parents - a int

Returns:

a double

localScoreDiff

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

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:

The score difference.

getPenaltyDiscount

public double getPenaltyDiscount()

Specialized scoring method for a single parent. Used to speed up the effect edges search.

Returns:

a double

setPenaltyDiscount

public void setPenaltyDiscount(double penaltyDiscount)

Setter for the field penaltyDiscount.

Parameters:

penaltyDiscount - a double

getCovariances

public ICovarianceMatrix getCovariances()

Getter for the field covariances.

Returns:

a ICovarianceMatrix object

getSampleSize

public int getSampleSize()

Getter for the field sampleSize.

Specified by:

getSampleSize in interface Score

Returns:

a int

isEffectEdge

public boolean isEffectEdge(double bump)

Returns true iff the edge between x and y is an effect edge.

Specified by:

isEffectEdge in interface Score

Parameters:

bump - The bump.

Returns:

True iff the edge between x and y is an effect edge.

getDataSet

public DataSet getDataSet()

getDataSet.

Returns:

a DataSet object

isVerbose

public boolean isVerbose()

isVerbose.

Returns:

a boolean

setVerbose

public void setVerbose(boolean verbose)

Setter for the field verbose.

Parameters:

verbose - a boolean

getVariables

public List<Node> getVariables()

The variables of the score.

Specified by:

getVariables in interface Score

Returns:

This list.

setVariables

public void setVariables(List<Node> variables)

Setter for the field variables.

Parameters:

variables - a List object

getMaxDegree

public int getMaxDegree()

Returns the max degree, by default 1000.

Specified by:

getMaxDegree in interface Score

Returns:

The max degree.

determines

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

Returns true iff the score determines the edge between x and y.

Specified by:

determines in interface Score

Parameters:

z - The set of nodes.

y - The node.

Returns:

True iff the score determines the edge between x and y.

getDeterminismThreshold

public double getDeterminismThreshold()

Getter for the field determinismThreshold.

Returns:

a double

setDeterminismThreshold

public void setDeterminismThreshold(double determinismThreshold)

Setter for the field determinismThreshold.

Parameters:

determinismThreshold - a double