Package edu.cmu.tetrad.algcomparison.statistic

Class BicDiffPerRecord

java.lang.Object

edu.cmu.tetrad.algcomparison.statistic.BicDiffPerRecord

All Implemented Interfaces:

Statistic, Serializable

public class BicDiffPerRecord
extends Object
implements Statistic

Difference between the true and estiamted BIC scores.

Version:

$Id: $Id

Author:

josephramsey

See Also:

• Serialized Form

Constructor Summary

Constructors

Constructor	Description
BicDiffPerRecord()	Constructs a new instance of the statistic.

Method Summary

Modifier and Type	Method	Description
String	getAbbreviation()	The abbreviation for the statistic.
String	getDescription()	Returns a short one-line description of this statistic.
double	getNormValue(double value)	Returns a mapping of the statistic to the interval [0, 1], with higher being better.
double	getValue(Graph trueGraph, Graph estGraph, DataModel dataModel)	Returns the value of this statistic, given the true graph and the estimated graph.
void	setPrecomputeCovariances(boolean precomputeCovariances)	Returns true if the covariances are precomputed.

Methods inherited from class java.lang.Object

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

Constructor Details

BicDiffPerRecord

public BicDiffPerRecord()

Constructs a new instance of the statistic.

Method Details

getAbbreviation

public String getAbbreviation()

The abbreviation for the statistic. This will be printed at the top of each column.

Specified by:

getAbbreviation in interface Statistic

Returns:

Thsi abbreviation.

getDescription

public String getDescription()

Returns a short one-line description of this statistic. This will be printed at the beginning of the report.

Specified by:

getDescription in interface Statistic

Returns:

This description.

getValue

public double getValue(Graph trueGraph,
 Graph estGraph,
 DataModel dataModel)

Returns the value of this statistic, given the true graph and the estimated graph.

Returns the difference between the true and estimated BIC scores, divided by the sample size.

Specified by:

getValue in interface Statistic

Parameters:

trueGraph - The true graph (DAG, CPDAG, PAG_of_the_true_DAG).

estGraph - The estimated graph (same type).

dataModel - The data model.

Returns:

The value of the statistic.

getNormValue

public double getNormValue(double value)

Returns a mapping of the statistic to the interval [0, 1], with higher being better. This is used for a calculation of a utility for an algorithm. If the statistic is already between 0 and 1, you can just return the statistic.

Returns the normalized value of the statistic.

Specified by:

getNormValue in interface Statistic

Parameters:

value - The value of the statistic.

Returns:

The weight of the statistic, 0 to 1, higher is better.

setPrecomputeCovariances

public void setPrecomputeCovariances(boolean precomputeCovariances)

Returns true if the covariances are precomputed.

Parameters:

precomputeCovariances - True if the covariances are precomputed.