gov.sandia.cognition.statistics.bayesian

Class RejectionSampling.ScalarEstimator.MinimizerFunction

java.lang.Object

gov.sandia.cognition.statistics.bayesian.RejectionSampling.ScalarEstimator.MinimizerFunction

All Implemented Interfaces:

Evaluator<java.lang.Double,java.lang.Double>

Enclosing class:

RejectionSampling.ScalarEstimator<ObservationType>

public class RejectionSampling.ScalarEstimator.MinimizerFunction
extends java.lang.Object
implements Evaluator<java.lang.Double,java.lang.Double>

Minimization function that measures the difference between the logarithm of the sampler function minus the logarithm of the conjunctive distribution.

Field Summary

Fields

Modifier and Type	Field and Description
protected ProbabilityFunction<java.lang.Double>	sampler Sampler function

Constructor Summary

Constructors

Constructor and Description
MinimizerFunction(ProbabilityFunction<java.lang.Double> sampler) Creates a new instance of MinimizerFunction

Method Summary

Modifier and Type	Method and Description
java.lang.Double	evaluate(java.lang.Double parameter) Evaluates the function on the given input and returns the output.

Methods inherited from class java.lang.Object

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

Field Detail

sampler

protected ProbabilityFunction<java.lang.Double> sampler

Sampler function

Constructor Detail

MinimizerFunction

public MinimizerFunction(ProbabilityFunction<java.lang.Double> sampler)

Creates a new instance of MinimizerFunction

Parameters:

sampler - Sampler function

Method Detail

evaluate

public java.lang.Double evaluate(java.lang.Double parameter)

Description copied from interface: Evaluator

Evaluates the function on the given input and returns the output.

Specified by:

evaluate in interface Evaluator<java.lang.Double,java.lang.Double>

Parameters:

parameter - The input to evaluate.

Returns:

The output produced by evaluating the input.