gov.sandia.cognition.statistics

Interface SmoothUnivariateDistribution

All Superinterfaces:

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

All Known Subinterfaces:

SmoothCumulativeDistributionFunction, UnivariateProbabilityDensityFunction

All Known Implementing Classes:

AbstractClosedFormSmoothUnivariateDistribution, BetaDistribution, BetaDistribution.CDF, BetaDistribution.PDF, CauchyDistribution, CauchyDistribution.CDF, CauchyDistribution.PDF, ChiSquareDistribution, ChiSquareDistribution.CDF, ChiSquareDistribution.PDF, ExponentialDistribution, ExponentialDistribution.CDF, ExponentialDistribution.PDF, GammaDistribution, GammaDistribution.CDF, GammaDistribution.PDF, InverseGammaDistribution, InverseGammaDistribution.CDF, InverseGammaDistribution.PDF, LaplaceDistribution, LaplaceDistribution.CDF, LaplaceDistribution.PDF, LogisticDistribution, LogisticDistribution.CDF, LogisticDistribution.PDF, LogNormalDistribution, LogNormalDistribution.CDF, LogNormalDistribution.PDF, ParetoDistribution, ParetoDistribution.CDF, ParetoDistribution.PDF, ScalarMixtureDensityModel, ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.PDF, StudentTDistribution, StudentTDistribution.CDF, StudentTDistribution.PDF, UniformDistribution, UniformDistribution.CDF, UniformDistribution.PDF, UnivariateGaussian, UnivariateGaussian.CDF, UnivariateGaussian.CDF.Inverse, UnivariateGaussian.PDF, WeibullDistribution, WeibullDistribution.CDF, WeibullDistribution.PDF

public interface SmoothUnivariateDistribution
extends ClosedFormUnivariateDistribution<java.lang.Double>, ClosedFormComputableDistribution<java.lang.Double>

A closed-form scalar distribution that is also smooth. That is, this type of distribution has a PDF and a CDF.

Since:

3.0

Author:

Kevin R. Dixon

Method Summary

Modifier and Type	Method and Description
SmoothCumulativeDistributionFunction	getCDF() Gets the CDF of a scalar distribution.
java.lang.Double	getMean() Gets the arithmetic mean, or "first central moment" or "expectation", of the distribution.
UnivariateProbabilityDensityFunction	getProbabilityFunction() Gets the distribution function associated with this Distribution, either the PDF or PMF.
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, double[] output, int start, int length) Samples values from this distribution as an array of doubles.

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

getMaxSupport, getMeanAsDouble, getMinSupport, getVariance

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

sample, sample, sampleInto

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

clone, convertFromVector, convertToVector

Method Detail

getProbabilityFunction

UnivariateProbabilityDensityFunction getProbabilityFunction()

Description copied from interface: ComputableDistribution

Gets the distribution function associated with this Distribution, either the PDF or PMF.

Specified by:

getProbabilityFunction in interface ComputableDistribution<java.lang.Double>

Returns:

Distribution function associated with this Distribution.

getCDF

SmoothCumulativeDistributionFunction getCDF()

Description copied from interface: UnivariateDistribution

Gets the CDF of a scalar distribution.

Specified by:

getCDF in interface ClosedFormUnivariateDistribution<java.lang.Double>

Specified by:

getCDF in interface UnivariateDistribution<java.lang.Double>

Returns:

CDF of the scalar distribution.

getMean

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>

Returns:

Mean of the distribution.

sampleAsDouble

double sampleAsDouble(java.util.Random random)

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

Parameters:

random - Random number generator to use.

Returns:

A value sampled from this distribution.

sampleAsDoubles

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

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

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

void sampleInto(java.util.Random random,
                double[] output,
                int start,
                int length)

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

Parameters:

random - Random number generator to use.

output - The array to write the result into. Cannot be null.

start - The offset in the array to start writing at. Cannot be negative.

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