gov.sandia.cognition.statistics

Class AbstractClosedFormSmoothUnivariateDistribution

java.lang.Object

gov.sandia.cognition.util.AbstractCloneableSerializable

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

gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution<java.lang.Double>

gov.sandia.cognition.statistics.AbstractClosedFormSmoothUnivariateDistribution

All Implemented Interfaces:

Vectorizable, ClosedFormComputableDistribution<java.lang.Double>, ClosedFormDistribution<java.lang.Double>, ClosedFormUnivariateDistribution<java.lang.Double>, ComputableDistribution<java.lang.Double>, Distribution<java.lang.Double>, DistributionWithMean<java.lang.Double>, SmoothUnivariateDistribution, UnivariateDistribution<java.lang.Double>, CloneableSerializable, java.io.Serializable, java.lang.Cloneable

Direct Known Subclasses:

BetaDistribution, CauchyDistribution, ChiSquareDistribution, ExponentialDistribution, GammaDistribution, InverseGammaDistribution, LaplaceDistribution, LogisticDistribution, LogNormalDistribution, ParetoDistribution, StudentTDistribution, UniformDistribution, UnivariateGaussian, WeibullDistribution

public abstract class AbstractClosedFormSmoothUnivariateDistribution
extends AbstractClosedFormUnivariateDistribution<java.lang.Double>
implements SmoothUnivariateDistribution

Partial implementation of SmoothUnivariateDistribution

Since:

3.0

Author:

Kevin R. Dixon

See Also:

Serialized Form

Constructor Summary

Constructors

Constructor and Description
AbstractClosedFormSmoothUnivariateDistribution()

Method Summary

Modifier and Type	Method and Description
java.lang.Double	getMean() Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
double	sampleAsDouble(java.util.Random random) Samples a value from this distribution as a double.
double[]	sampleAsDoubles(java.util.Random random, int count) Samples values from this distribution as an array of doubles.
void	sampleInto(java.util.Random random, int sampleCount, java.util.Collection<? super java.lang.Double> output) Draws multiple random samples from the distribution and puts the result into the given collection.

Methods inherited from class gov.sandia.cognition.statistics.AbstractClosedFormUnivariateDistribution

clone

Methods inherited from class gov.sandia.cognition.statistics.AbstractDistribution

sample, sample

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.SmoothUnivariateDistribution

getCDF, getProbabilityFunction, sampleInto

Methods inherited from interface gov.sandia.cognition.statistics.UnivariateDistribution

getMaxSupport, getMeanAsDouble, getMinSupport, getVariance

Methods inherited from interface gov.sandia.cognition.statistics.Distribution

sample, sample

Methods inherited from interface gov.sandia.cognition.math.matrix.Vectorizable

clone, convertFromVector, convertToVector

Constructor Detail

AbstractClosedFormSmoothUnivariateDistribution

public AbstractClosedFormSmoothUnivariateDistribution()

Method Detail

getMean

public java.lang.Double getMean()

Description copied from interface: DistributionWithMean

Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.

Specified by:

getMean in interface DistributionWithMean<java.lang.Double>

Specified by:

getMean in interface SmoothUnivariateDistribution

Returns:

Mean of the distribution.

sampleAsDouble

public double sampleAsDouble(java.util.Random random)

Description copied from interface: SmoothUnivariateDistribution

Samples a value from this distribution as a double. This is a convenience method to potentially avoid boxing.

Specified by:

sampleAsDouble in interface SmoothUnivariateDistribution

Parameters:

random - Random number generator to use.

Returns:

A value sampled from this distribution.

sampleAsDoubles

public double[] sampleAsDoubles(java.util.Random random,
                                int count)

Description copied from interface: SmoothUnivariateDistribution

Samples values from this distribution as an array of doubles. This is a convenience method to potentially avoid boxing.

Specified by:

sampleAsDoubles in interface SmoothUnivariateDistribution

Parameters:

random - Random number generator to use.

count - The number of values to sample. Cannot be negative

Returns:

An array of values sampled from this distribution. Size is that of count.

sampleInto

public void sampleInto(java.util.Random random,
                       int sampleCount,
                       java.util.Collection<? super java.lang.Double> output)

Description copied from interface: Distribution

Draws multiple random samples from the distribution and puts the result into the given collection.

Specified by:

sampleInto in interface Distribution<java.lang.Double>

Parameters:

random - Random number generator to use.

sampleCount - The number of samples to draw. Cannot be negative.

output - The collection to add the samples into.