Uses of Interface
gov.sandia.cognition.statistics.ClosedFormDistribution

Packages that use ClosedFormDistribution

Package	Description
gov.sandia.cognition.statistics	Provides the inheritance hierarchy for general statistical methods and distributions.
gov.sandia.cognition.statistics.bayesian	Provides algorithms for computing Bayesian estimates of parameters.
gov.sandia.cognition.statistics.bayesian.conjugate	Provides Bayesian estimation routines based on conjugate prior distribution of parameters of specific conditional distributions.
gov.sandia.cognition.statistics.distribution	Provides statistical distributions.
gov.sandia.cognition.statistics.method	Provides algorithms for evaluating statistical data and conducting statistical inference, particularly frequentist methods.

Uses of ClosedFormDistribution in gov.sandia.cognition.statistics

Classes in gov.sandia.cognition.statistics with type parameters of type ClosedFormDistribution

Modifier and Type	Class and Description
class	DefaultDistributionParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>> Default implementation of DistributionParameter using introspection.

Subinterfaces of ClosedFormDistribution in gov.sandia.cognition.statistics

Modifier and Type	Interface and Description
interface	ClosedFormComputableDiscreteDistribution<DataType> A discrete, closed-form Distribution with a PMF.
interface	ClosedFormComputableDistribution<DataType> A closed-form Distribution that also has an associated distribution function.
interface	ClosedFormCumulativeDistributionFunction<DomainType extends java.lang.Number> Functionality of a cumulative distribution function that's defined with closed-form parameters.
interface	ClosedFormDiscreteUnivariateDistribution<DomainType extends java.lang.Number> A ClosedFormUnivariateDistribution that is also a DiscreteDistribution
interface	ClosedFormUnivariateDistribution<NumberType extends java.lang.Number> Defines the functionality associated with a closed-form scalar distribution.
interface	ProbabilityDensityFunction<DataType> Defines a probability density function.
interface	SmoothCumulativeDistributionFunction This defines a CDF that has an associated derivative, which is its PDF.
interface	SmoothUnivariateDistribution A closed-form scalar distribution that is also smooth.
interface	UnivariateProbabilityDensityFunction A PDF that takes doubles as input.

Classes in gov.sandia.cognition.statistics that implement ClosedFormDistribution

Modifier and Type	Class and Description
class	AbstractClosedFormIntegerDistribution An abstract class for closed-form integer distributions.
class	AbstractClosedFormSmoothUnivariateDistribution Partial implementation of SmoothUnivariateDistribution
class	AbstractClosedFormUnivariateDistribution<NumberType extends java.lang.Number> Partial implementation of a ClosedFormUnivariateDistribution.

Fields in gov.sandia.cognition.statistics declared as ClosedFormDistribution

Modifier and Type	Field and Description
protected ConditionalType	DefaultDistributionParameter.conditionalDistribution Distribution from which to pull the parameters.

Uses of ClosedFormDistribution in gov.sandia.cognition.statistics.bayesian

Classes in gov.sandia.cognition.statistics.bayesian with type parameters of type ClosedFormDistribution

Modifier and Type	Class and Description
class	AbstractBayesianParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>,PriorType extends Distribution<ParameterType>> Partial implementation of BayesianParameter
class	DefaultBayesianParameter<ParameterType,ConditionalType extends ClosedFormDistribution<?>,PriorType extends Distribution<ParameterType>> Default implementation of BayesianParameter using reflection.

Fields in gov.sandia.cognition.statistics.bayesian declared as ClosedFormDistribution

Modifier and Type	Field and Description
protected ConditionalType	AbstractBayesianParameter.conditionalDistribution Distribution from which to pull the parameters.

Methods in gov.sandia.cognition.statistics.bayesian with type parameters of type ClosedFormDistribution

Modifier and Type	Method and Description
static <ParameterType,ConditionalType extends ClosedFormDistribution<?>,PriorType extends Distribution<ParameterType>> DefaultBayesianParameter<ParameterType,ConditionalType,PriorType>	DefaultBayesianParameter.create(ConditionalType conditionalDistribution, java.lang.String parameterName, PriorType parameterPrior) Creates a new instance of DefaultBayesianParameter

Methods in gov.sandia.cognition.statistics.bayesian that return types with arguments of type ClosedFormDistribution

Modifier and Type	Method and Description
Evaluator<? super Vectorizable,? extends ClosedFormDistribution<OutputType>>	BayesianRegression.createPredictiveDistribution(PosteriorType posterior) Creates the predictive distribution of outputs given the weight posterior

Methods in gov.sandia.cognition.statistics.bayesian with parameters of type ClosedFormDistribution

Modifier and Type	Method and Description
static <ObservationType,ParameterType> java.util.ArrayList<? extends ObservationType>	BayesianUtil.sample(ClosedFormDistribution<ObservationType> conditional, java.lang.String parameterName, Distribution<ParameterType> prior, java.util.Random random, int numSamples) Samples from the given BayesianParameter by first sampling the prior distribution, then updating the conditional distribution, then sampling from the updated conditional distribution.

Uses of ClosedFormDistribution in gov.sandia.cognition.statistics.bayesian.conjugate

Classes in gov.sandia.cognition.statistics.bayesian.conjugate with type parameters of type ClosedFormDistribution

Modifier and Type	Class and Description
class	AbstractConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> Partial implementation of ConjugatePriorBayesianEstimator that contains a initial belief (prior) distribution function.
class	AbstractConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> Partial implementation of ConjugatePriorBayesianEstimator that contains a initial belief (prior) distribution function.
interface	ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> A Bayesian Estimator that makes use of conjugate priors, which is a mathematical trick when the conditional and the prior result a posterior that is the same type as the prior.
interface	ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> A Bayesian Estimator that makes use of conjugate priors, which is a mathematical trick when the conditional and the prior result a posterior that is the same type as the prior.
interface	ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> A conjugate prior estimator that also has a closed-form predictive posterior.
interface	ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>> A conjugate prior estimator that also has a closed-form predictive posterior.

Uses of ClosedFormDistribution in gov.sandia.cognition.statistics.distribution

Classes in gov.sandia.cognition.statistics.distribution that implement ClosedFormDistribution

Modifier and Type	Class and Description
class	BernoulliDistribution A Bernoulli distribution, which takes a value of "1" with probability "p" and value of "0" with probability "1-p".
static class	BernoulliDistribution.CDF CDF of a Bernoulli distribution.
static class	BernoulliDistribution.PMF PMF of the Bernoulli distribution.
class	BetaBinomialDistribution A Binomial distribution where the binomial parameter, p, is set according to a Beta distribution instead of a single value.
static class	BetaBinomialDistribution.CDF CDF of BetaBinomialDistribution
static class	BetaBinomialDistribution.PMF PMF of the BetaBinomialDistribution
class	BetaDistribution Computes the Beta-family of probability distributions.
static class	BetaDistribution.CDF CDF of the Beta-family distribution
static class	BetaDistribution.PDF Beta distribution probability density function
class	BinomialDistribution Binomial distribution, which is a collection of Bernoulli trials
static class	BinomialDistribution.CDF CDF of the Binomial distribution, which is the probability of getting up to "x" successes in "N" trials with a Bernoulli probability of "p"
static class	BinomialDistribution.PMF The Probability Mass Function of a binomial distribution.
class	CategoricalDistribution The Categorical Distribution is the multivariate generalization of the Bernoulli distribution, where the outcome of an experiment is a one-of-N output, where the output is a selector Vector.
static class	CategoricalDistribution.PMF PMF of the Categorical Distribution
class	CauchyDistribution A Cauchy Distribution is the ratio of two Gaussian Distributions, sometimes known as the Lorentz distribution.
static class	CauchyDistribution.CDF CDF of the CauchyDistribution.
static class	CauchyDistribution.PDF PDF of the CauchyDistribution.
class	ChineseRestaurantProcess A Chinese Restaurant Process is a discrete stochastic processes that partitions data points to clusters.
static class	ChineseRestaurantProcess.PMF PMF of the Chinese Restaurant Process
class	ChiSquareDistribution Describes a Chi-Square Distribution.
static class	ChiSquareDistribution.CDF Cumulative Distribution Function (CDF) of a Chi-Square Distribution
static class	ChiSquareDistribution.PDF PDF of the Chi-Square distribution
class	DeterministicDistribution A deterministic distribution that returns samples at a single point.
static class	DeterministicDistribution.CDF CDF of the deterministic distribution.
static class	DeterministicDistribution.PMF PMF of the deterministic distribution.
class	DirichletDistribution The Dirichlet distribution is the multivariate generalization of the beta distribution.
static class	DirichletDistribution.PDF PDF of the Dirichlet distribution.
class	ExponentialDistribution An Exponential distribution describes the time between events in a poisson process, resulting in a memoryless distribution.
static class	ExponentialDistribution.CDF CDF of the ExponentialDistribution.
static class	ExponentialDistribution.PDF PDF of the ExponentialDistribution.
class	GammaDistribution Class representing the Gamma distribution.
static class	GammaDistribution.CDF CDF of the Gamma distribution
static class	GammaDistribution.PDF Closed-form PDF of the Gamma distribution
class	GeometricDistribution The geometric distribution models the number of successes before the first failure occurs under an independent succession of Bernoulli tests.
static class	GeometricDistribution.CDF CDF of the Geometric distribution
static class	GeometricDistribution.PMF PMF of the Geometric distribution
class	InverseGammaDistribution Defines an inverse-gamma distribution.
static class	InverseGammaDistribution.CDF CDF of the inverseRootFinder-gamma distribution.
static class	InverseGammaDistribution.PDF PDF of the inverseRootFinder-Gamma distribution.
class	InverseWishartDistribution The Inverse-Wishart distribution is the multivariate generalization of the inverse-gamma distribution.
static class	InverseWishartDistribution.PDF PDF of the Inverse-Wishart distribution, though I have absolutely no idea why anybody would evaluate the PDF of an Inverse-Wishart...
class	KolmogorovDistribution Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test.
static class	KolmogorovDistribution.CDF Contains the Cumulative Distribution Function description for the "D" statistic used within the Kolmogorov-Smirnov test.
class	LaplaceDistribution A Laplace distribution, sometimes called a double exponential distribution.
static class	LaplaceDistribution.CDF CDF of the Laplace distribution.
static class	LaplaceDistribution.PDF The PDF of a Laplace Distribution.
class	LogisticDistribution A implementation of the scalar logistic distribution, which measures the log-odds of a binary event.
static class	LogisticDistribution.CDF CDF of the LogisticDistribution
static class	LogisticDistribution.PDF PDF of the LogisticDistribution
class	LogNormalDistribution Log-Normal distribution PDF and CDF implementations.
static class	LogNormalDistribution.CDF CDF of the Log-Normal Distribution
static class	LogNormalDistribution.PDF PDF of a Log-normal distribution
static class	MixtureOfGaussians.PDF PDF of the MixtureOfGaussians
class	MultinomialDistribution A multinomial distribution is the multivariate/multiclass generalization of the Binomial distribution.
static class	MultinomialDistribution.PMF Probability Mass Function of the Multinomial Distribution.
class	MultivariateGaussian The MultivariateGaussian class implements a multidimensional Gaussian distribution that contains a mean vector and a covariance matrix.
static class	MultivariateGaussian.PDF PDF of a multivariate Gaussian
class	MultivariateGaussianInverseGammaDistribution A distribution where the mean is selected by a multivariate Gaussian and a variance parameter (either for a univariate Gaussian or isotropic Gaussian) is determined by an Inverse-Gamma distribution.
class	MultivariateMixtureDensityModel<DistributionType extends ClosedFormComputableDistribution<Vector>> A LinearMixtureModel of multivariate distributions with associated PDFs.
static class	MultivariateMixtureDensityModel.PDF<DistributionType extends ClosedFormComputableDistribution<Vector>> PDF of the MultivariateMixtureDensityModel
class	MultivariatePolyaDistribution A multivariate Polya Distribution, also known as a Dirichlet-Multinomial model, is a compound distribution where the parameters of a multinomial are drawn from a Dirichlet distribution with fixed parameters and a constant number of trials and then the observations are generated by this multinomial.
static class	MultivariatePolyaDistribution.PMF PMF of the MultivariatePolyaDistribution
class	MultivariateStudentTDistribution Multivariate generalization of the noncentral Student's t-distribution.
static class	MultivariateStudentTDistribution.PDF PDF of the MultivariateStudentTDistribution
class	NegativeBinomialDistribution Negative binomial distribution, also known as the Polya distribution, gives the number of successes of a series of Bernoulli trials before recording a given number of failures.
static class	NegativeBinomialDistribution.CDF CDF of the NegativeBinomialDistribution
static class	NegativeBinomialDistribution.PMF PMF of the NegativeBinomialDistribution.
class	NormalInverseGammaDistribution The normal inverse-gamma distribution is the product of a univariate Gaussian distribution with an inverse-gamma distribution.
static class	NormalInverseGammaDistribution.PDF PDF of the NormalInverseGammaDistribution
class	NormalInverseWishartDistribution The normal inverse Wishart distribution
static class	NormalInverseWishartDistribution.PDF PDF of the normal inverse-Wishart distribution.
class	ParetoDistribution This class describes the Pareto distribution, sometimes called the Bradford Distribution.
static class	ParetoDistribution.CDF CDF of the Pareto Distribution.
static class	ParetoDistribution.PDF PDF of the ParetoDistribution
class	PoissonDistribution A Poisson distribution is the limits of what happens when a Bernoulli trial with "rare" events are sampled on a continuous basis and then binned into discrete time intervals.
static class	PoissonDistribution.CDF CDF of the PoissonDistribution
static class	PoissonDistribution.PMF PMF of the PoissonDistribution.
class	ScalarMixtureDensityModel ScalarMixtureDensityModel (SMDM) implements just that: a scalar mixture density model.
static class	ScalarMixtureDensityModel.CDF CDFof the SMDM
static class	ScalarMixtureDensityModel.PDF PDF of the SMDM
class	SnedecorFDistribution CDF of the Snedecor F-distribution (also known as Fisher F-distribution, Fisher-Snedecor F-distribution, or just plain old F-distribution).
static class	SnedecorFDistribution.CDF CDF of the F-distribution.
class	StudentizedRangeDistribution Implementation of the Studentized Range distribution, which defines the population correction factor when performing multiple comparisons.
static class	StudentizedRangeDistribution.CDF CDF of the StudentizedRangeDistribution
class	StudentTDistribution Defines a noncentral Student-t Distribution.
static class	StudentTDistribution.CDF Evaluator that computes the Cumulative Distribution Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
static class	StudentTDistribution.PDF Evaluator that computes the Probability Density Function (CDF) of a Student-t distribution with a fixed number of degrees of freedom
class	UniformDistribution Contains the (very simple) definition of a continuous Uniform distribution, parameterized between the minimum and maximum bounds.
static class	UniformDistribution.CDF Cumulative Distribution Function of a uniform
static class	UniformDistribution.PDF Probability density function of a Uniform Distribution
class	UniformIntegerDistribution Contains the (very simple) definition of a continuous Uniform distribution, parameterized between the minimum and maximum bounds.
static class	UniformIntegerDistribution.CDF Implements the cumulative distribution function for the discrete uniform distribution.
static class	UniformIntegerDistribution.PMF Probability mass function of a discrete uniform distribution.
class	UnivariateGaussian This class contains internal classes that implement useful functions based on the Gaussian distribution.
static class	UnivariateGaussian.CDF CDF of the underlying Gaussian.
static class	UnivariateGaussian.CDF.Inverse Inverts the CumulativeDistribution function.
static class	UnivariateGaussian.PDF PDF of the underlying Gaussian.
class	WeibullDistribution Describes a Weibull distribution, which is often used to describe the mortality, lifespan, or size distribution of objects.
static class	WeibullDistribution.CDF CDF of the Weibull distribution
static class	WeibullDistribution.PDF PDF of the Weibull distribution
class	YuleSimonDistribution The Yule-Simon distribution is a model of preferential attachment, such as a model of the number of groups follows a power-law distribution (Zipf's Law).
static class	YuleSimonDistribution.CDF CDF of the Yule-Simon Distribution
static class	YuleSimonDistribution.PMF PMF of the Yule-Simon Distribution

Uses of ClosedFormDistribution in gov.sandia.cognition.statistics.method

Classes in gov.sandia.cognition.statistics.method with type parameters of type ClosedFormDistribution

Modifier and Type	Class and Description
class	DistributionParameterEstimator<DataType,DistributionType extends ClosedFormDistribution<? extends DataType>> A method of estimating the parameters of a distribution using an arbitrary CostFunction and FunctionMinimizer algorithm.

Fields in gov.sandia.cognition.statistics.method declared as ClosedFormDistribution

Modifier and Type	Field and Description
protected DistributionType	DistributionParameterEstimator.DistributionWrapper.distribution Distribution to estimate the parameters of