gov.sandia.cognition.statistics.montecarlo

Class MultivariateMonteCarloIntegrator

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.montecarlo.MultivariateMonteCarloIntegrator

All Implemented Interfaces:

MonteCarloIntegrator<Vector>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

public class MultivariateMonteCarloIntegrator
extends AbstractCloneableSerializable
implements MonteCarloIntegrator<Vector>

A Monte Carlo integrator for multivariate (vector) outputs.

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Field Summary

Fields

Modifier and Type	Field and Description
static double	DEFAULT_VARIANCE Default variance to add to the Gaussian, 0.0.
static MultivariateMonteCarloIntegrator	INSTANCE Default instance because this class has no state.

Constructor Summary

Constructors

Constructor and Description
MultivariateMonteCarloIntegrator() Creates a new instance of MultivariateMonteCarloIntegrator

Method Summary

Modifier and Type	Method and Description
MultivariateGaussian.PDF	getMean(java.util.Collection<? extends Vector> samples) Computes the Monte Carlo distribution of the given samples.
MultivariateGaussian.PDF	getMean(java.util.List<? extends WeightedValue<? extends Vector>> samples) Computes the Monte Carlo distribution of the given weighted samples.
<SampleType> MultivariateGaussian.PDF	integrate(java.util.Collection<? extends SampleType> samples, Evaluator<? super SampleType,? extends Vector> expectationFunction) Integrates the given function given samples from another function.
<SampleType> MultivariateGaussian.PDF	integrate(java.util.List<? extends WeightedValue<? extends SampleType>> samples, Evaluator<? super SampleType,? extends Vector> expectationFunction) Integrates the given function given weighted samples from another function.

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

DEFAULT_VARIANCE

public static final double DEFAULT_VARIANCE

Default variance to add to the Gaussian, 0.0.

See Also:

Constant Field Values

INSTANCE

public static final MultivariateMonteCarloIntegrator INSTANCE

Default instance because this class has no state.

Constructor Detail

MultivariateMonteCarloIntegrator

public MultivariateMonteCarloIntegrator()

Creates a new instance of MultivariateMonteCarloIntegrator

Method Detail

integrate

public <SampleType> MultivariateGaussian.PDF integrate(java.util.Collection<? extends SampleType> samples,
                                                       Evaluator<? super SampleType,? extends Vector> expectationFunction)

Description copied from interface: MonteCarloIntegrator

Integrates the given function given samples from another function.

Specified by:

integrate in interface MonteCarloIntegrator<Vector>

Type Parameters:

SampleType - Type of samples to consider.

Parameters:

samples - Samples from the underlying distribution.

expectationFunction - Function for which to compute the expectation.

Returns:

Distribution of the integration.

integrate

public <SampleType> MultivariateGaussian.PDF integrate(java.util.List<? extends WeightedValue<? extends SampleType>> samples,
                                                       Evaluator<? super SampleType,? extends Vector> expectationFunction)

Description copied from interface: MonteCarloIntegrator

Integrates the given function given weighted samples from another function.

Specified by:

integrate in interface MonteCarloIntegrator<Vector>

Type Parameters:

SampleType - Type of samples to consider.

Parameters:

samples - Weighted samples from the underlying distribution.

expectationFunction - Function for which to compute the expectation.

Returns:

Distribution of the integration.

getMean

public MultivariateGaussian.PDF getMean(java.util.Collection<? extends Vector> samples)

Description copied from interface: MonteCarloIntegrator

Computes the Monte Carlo distribution of the given samples.

Specified by:

getMean in interface MonteCarloIntegrator<Vector>

Parameters:

samples - Samples to consider.

Returns:

Distribution describing the samples.

getMean

public MultivariateGaussian.PDF getMean(java.util.List<? extends WeightedValue<? extends Vector>> samples)

Description copied from interface: MonteCarloIntegrator

Computes the Monte Carlo distribution of the given weighted samples.

Specified by:

getMean in interface MonteCarloIntegrator<Vector>

Parameters:

samples - Weighted samples to consider.

Returns:

Distribution describing the samples.