gov.sandia.cognition.statistics.montecarlo

Class DirectSampler<DataType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.montecarlo.DirectSampler<DataType>

Type Parameters:

DataType - Type of data to sample.

All Implemented Interfaces:

MonteCarloSampler<DataType,DataType,ProbabilityFunction<DataType>>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

public class DirectSampler<DataType>
extends AbstractCloneableSerializable
implements MonteCarloSampler<DataType,DataType,ProbabilityFunction<DataType>>

Sampler that generates samples directly from a target distribution.

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Constructor Summary

Constructors

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

Method Summary

Modifier and Type	Method and Description
java.util.ArrayList<? extends DataType>	sample(ProbabilityFunction<DataType> targetFunction, java.util.Random random, int numSamples) Draws samples according to the distribution of the target 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

Constructor Detail

DirectSampler

public DirectSampler()

Creates a new instance of DirectSampler

Method Detail

sample

public java.util.ArrayList<? extends DataType> sample(ProbabilityFunction<DataType> targetFunction,
                                                      java.util.Random random,
                                                      int numSamples)

Description copied from interface: MonteCarloSampler

Draws samples according to the distribution of the target function.

Specified by:

sample in interface MonteCarloSampler<DataType,DataType,ProbabilityFunction<DataType>>

Parameters:

targetFunction - Target function that we want to generate samples.

random - Random-number generator.

numSamples - Number of samples to generate.

Returns:

Samples