gov.sandia.cognition.statistics

Class AbstractDistribution<DataType>

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

gov.sandia.cognition.statistics.AbstractDistribution<DataType>

Type Parameters:

DataType - Type of data that can be sampled from the Distribution.

All Implemented Interfaces:

Distribution<DataType>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

AbstractClosedFormUnivariateDistribution, CategoricalDistribution, ChineseRestaurantProcess, DirichletDistribution, InverseWishartDistribution, LinearMixtureModel, MaximumAPosterioriCategorizer, MultinomialDistribution, MultivariateGaussian, MultivariateGaussianInverseGammaDistribution, MultivariatePolyaDistribution, MultivariateStudentTDistribution, NormalInverseGammaDistribution, NormalInverseWishartDistribution

public abstract class AbstractDistribution<DataType>
extends AbstractCloneableSerializable
implements Distribution<DataType>

Partial implementation of Distribution.

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractDistribution()

Method Summary

Modifier and Type	Method and Description
DataType	sample(java.util.Random random) Draws a single random sample from the distribution.
java.util.ArrayList<DataType>	sample(java.util.Random random, int numSamples) Draws multiple random samples from the distribution.

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.statistics.Distribution

sampleInto

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

clone

Constructor Detail

AbstractDistribution

public AbstractDistribution()

Method Detail

sample

public DataType sample(java.util.Random random)

Description copied from interface: Distribution

Draws a single random sample from the distribution.

Specified by:

sample in interface Distribution<DataType>

Parameters:

random - Random-number generator to use in order to generate random numbers.

Returns:

Sample drawn according to this distribution.

sample

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

Description copied from interface: Distribution

Draws multiple random samples from the distribution. It is generally more efficient to use this multiple-sample method than multiple calls of the single-sample method. (But not always.)

Specified by:

sample in interface Distribution<DataType>

Parameters:

random - Random-number generator to use in order to generate random numbers.

numSamples - Number of samples to draw from the distribution.

Returns:

Samples drawn according to this distribution.