gov.sandia.cognition.statistics
Interface UnivariateDistribution<NumberType extends Number>

Type Parameters:
NumberType - Type of Number that can be sampled from this distribution.
All Superinterfaces:
Cloneable, CloneableSerializable, Distribution<NumberType>, DistributionWithMean<NumberType>, Serializable
All Known Subinterfaces:
ClosedFormCumulativeDistributionFunction<DomainType>, ClosedFormDiscreteUnivariateDistribution<DomainType>, ClosedFormUnivariateDistribution<NumberType>, CumulativeDistributionFunction<NumberType>, InvertibleCumulativeDistributionFunction<NumberType>, SmoothCumulativeDistributionFunction, SmoothUnivariateDistribution, UnivariateProbabilityDensityFunction
All Known Implementing Classes:
AbstractClosedFormSmoothUnivariateDistribution, AbstractClosedFormUnivariateDistribution, BernoulliDistribution, BernoulliDistribution.CDF, BernoulliDistribution.PMF, BetaBinomialDistribution, BetaBinomialDistribution.CDF, BetaBinomialDistribution.PMF, BetaDistribution, BetaDistribution.CDF, BetaDistribution.PDF, BinomialDistribution, BinomialDistribution.CDF, BinomialDistribution.PMF, CauchyDistribution, CauchyDistribution.CDF, CauchyDistribution.PDF, ChiSquareDistribution, ChiSquareDistribution.CDF, ChiSquareDistribution.PDF, DeterministicDistribution, DeterministicDistribution.CDF, DeterministicDistribution.PMF, ExponentialDistribution, ExponentialDistribution.CDF, ExponentialDistribution.PDF, GammaDistribution, GammaDistribution.CDF, GammaDistribution.PDF, GeometricDistribution, GeometricDistribution.CDF, GeometricDistribution.PMF, InverseGammaDistribution, InverseGammaDistribution.CDF, InverseGammaDistribution.PDF, KolmogorovDistribution, KolmogorovDistribution.CDF, LaplaceDistribution, LaplaceDistribution.CDF, LaplaceDistribution.PDF, LogisticDistribution, LogisticDistribution.CDF, LogisticDistribution.PDF, LogNormalDistribution, LogNormalDistribution.CDF, LogNormalDistribution.PDF, NegativeBinomialDistribution, NegativeBinomialDistribution.CDF, NegativeBinomialDistribution.PMF, ParetoDistribution, ParetoDistribution.CDF, ParetoDistribution.PDF, PoissonDistribution, PoissonDistribution.CDF, PoissonDistribution.PMF, ScalarDataDistribution, ScalarDataDistribution.CDF, ScalarDataDistribution.PMF, ScalarMixtureDensityModel, ScalarMixtureDensityModel.CDF, ScalarMixtureDensityModel.PDF, SnedecorFDistribution, SnedecorFDistribution.CDF, StudentizedRangeDistribution, StudentizedRangeDistribution.CDF, StudentTDistribution, StudentTDistribution.CDF, StudentTDistribution.PDF, UniformDistribution, UniformDistribution.CDF, UniformDistribution.PDF, UnivariateGaussian, UnivariateGaussian.CDF, UnivariateGaussian.CDF.Inverse, UnivariateGaussian.PDF, UnivariateRandomVariable, WeibullDistribution, WeibullDistribution.CDF, WeibullDistribution.PDF, YuleSimonDistribution, YuleSimonDistribution.CDF, YuleSimonDistribution.PMF

public interface UnivariateDistribution<NumberType extends Number>
extends DistributionWithMean<NumberType>

A Distribution that takes Doubles as inputs and can compute its variance.

Since:
3.0
Author:
Kevin R. Dixon

Method Summary
 CumulativeDistributionFunction<NumberType> getCDF()
          Gets the CDF of a scalar distribution.
 NumberType getMaxSupport()
          Gets the minimum support (domain or input) of the distribution.
 NumberType getMinSupport()
          Gets the minimum support (domain or input) of the distribution.
 double getVariance()
          Gets the variance of the distribution.
 
Methods inherited from interface gov.sandia.cognition.statistics.DistributionWithMean
getMean
 
Methods inherited from interface gov.sandia.cognition.statistics.Distribution
sample, sample
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone
 

Method Detail

getMinSupport

NumberType getMinSupport()
Gets the minimum support (domain or input) of the distribution.

Returns:
Minimum support.

getMaxSupport

NumberType getMaxSupport()
Gets the minimum support (domain or input) of the distribution.

Returns:
Minimum support.

getCDF

CumulativeDistributionFunction<NumberType> getCDF()
Gets the CDF of a scalar distribution.

Returns:
CDF of the scalar distribution.

getVariance

double getVariance()
Gets the variance of the distribution. This is sometimes called the second central moment by more pedantic people, which is equivalent to the square of the standard deviation.

Returns:
Variance of the distribution.