gov.sandia.cognition.statistics.bayesian

Class ImportanceSampling.DefaultUpdater<ObservationType,ParameterType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.bayesian.ImportanceSampling.DefaultUpdater<ObservationType,ParameterType>

Type Parameters:

ObservationType - Type of observation

ParameterType - Type of parameters to infer

All Implemented Interfaces:

ImportanceSampling.Updater<ObservationType,ParameterType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Enclosing class:

ImportanceSampling<ObservationType,ParameterType>

public static class ImportanceSampling.DefaultUpdater<ObservationType,ParameterType>
extends AbstractCloneableSerializable
implements ImportanceSampling.Updater<ObservationType,ParameterType>

Default ImportanceSampling Updater that uses a BayesianParameter to compute the quantities of interest.

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
protected BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	conjuctive Defines the parameter that connects the conditional and prior distributions.

Constructor Summary

Constructors

Constructor and Description
DefaultUpdater() Default constructor.
DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Creates a new instance of DefaultUpdater

Method Summary

Modifier and Type	Method and Description
double	computeLogImportanceValue(ParameterType parameter) Computes the parameter's importance weight.
double	computeLogLikelihood(ParameterType parameter, java.lang.Iterable<? extends ObservationType> data) Computes the log likelihood of the data given the parameter
BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	getConjuctive() Getter for conjunctive
ParameterType	makeProposal(java.util.Random random) Samples from the parameter prior
void	setConjuctive(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Setter for conjunctive

Methods inherited from class gov.sandia.cognition.util.AbstractCloneableSerializable

clone

Methods inherited from class java.lang.Object

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

Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable

clone

Field Detail

conjuctive

protected BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive

Defines the parameter that connects the conditional and prior distributions.

Constructor Detail

DefaultUpdater

public DefaultUpdater()

Default constructor.

DefaultUpdater

public DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive)

Creates a new instance of DefaultUpdater

Parameters:

conjuctive - Defines the parameter that connects the conditional and prior distributions.

Method Detail

computeLogLikelihood

public double computeLogLikelihood(ParameterType parameter,
                                   java.lang.Iterable<? extends ObservationType> data)

Description copied from interface: ImportanceSampling.Updater

Computes the log likelihood of the data given the parameter

Specified by:

computeLogLikelihood in interface ImportanceSampling.Updater<ObservationType,ParameterType>

Parameters:

parameter - Parameter to consider

data - Data to consider

Returns:

log likelihood of the data given the parameter

computeLogImportanceValue

public double computeLogImportanceValue(ParameterType parameter)

Description copied from interface: ImportanceSampling.Updater

Computes the parameter's importance weight.

Specified by:

computeLogImportanceValue in interface ImportanceSampling.Updater<ObservationType,ParameterType>

Parameters:

parameter - Parameter to consider

Returns:

Importance value

makeProposal

public ParameterType makeProposal(java.util.Random random)

Description copied from interface: ImportanceSampling.Updater

Samples from the parameter prior

Specified by:

makeProposal in interface ImportanceSampling.Updater<ObservationType,ParameterType>

Parameters:

random - Random number generator.

Returns:

Location of the proposed sample

getConjuctive

public BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> getConjuctive()

Getter for conjunctive

Returns:

Defines the parameter that connects the conditional and prior distributions.

setConjuctive

public void setConjuctive(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive)

Setter for conjunctive

Parameters:

conjuctive - Defines the parameter that connects the conditional and prior distributions.