Uses of Interface
gov.sandia.cognition.statistics.bayesian.BayesianParameter

Packages that use BayesianParameter

Package	Description
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.

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

Classes in gov.sandia.cognition.statistics.bayesian that implement BayesianParameter

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 BayesianParameter

Modifier and Type	Field and Description
protected BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	ImportanceSampling.DefaultUpdater.conjuctive Defines the parameter that connects the conditional and prior distributions.
protected BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	RejectionSampling.DefaultUpdater.conjuctive Defines the parameter that connects the conditional and prior distributions.

Methods in gov.sandia.cognition.statistics.bayesian that return BayesianParameter

Modifier and Type	Method and Description
BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	ImportanceSampling.DefaultUpdater.getConjuctive() Getter for conjunctive
BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>>	RejectionSampling.DefaultUpdater.getConjuctive() Getter for conjunctive

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

Modifier and Type	Method and Description
static <ObservationType,ParameterType> UnivariateGaussian	BayesianUtil.expectedDeviance(BayesianParameter<ParameterType,? extends ComputableDistribution<ObservationType>,?> predictiveDistribution, java.lang.Iterable<? extends ObservationType> observations, java.util.Random random, int numSamples) Computes the expected deviance of the model by sampling parameters from the posterior and then computing the deviance using the conditional distribution.
static <ObservationType,ParameterType> java.util.ArrayList<ObservationType>	BayesianUtil.sample(BayesianParameter<ParameterType,? extends Distribution<ObservationType>,? extends Distribution<ParameterType>> parameter, 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.
void	ImportanceSampling.DefaultUpdater.setConjuctive(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Setter for conjunctive
void	RejectionSampling.DefaultUpdater.setConjuctive(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Setter for conjunctive

Constructors in gov.sandia.cognition.statistics.bayesian with parameters of type BayesianParameter

Constructor and Description
DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Creates a new instance of DefaultUpdater
DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive) Creates a new instance of DefaultUpdater
DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive, java.lang.Double scale, ProbabilityFunction<ParameterType> sampler) Creates a new instance of DefaultUpdater
DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive, ProbabilityFunction<ParameterType> sampler) Creates a new instance of DefaultUpdater
ScalarEstimator(BayesianParameter<java.lang.Double,? extends ProbabilityFunction<ObservationType>,? extends UnivariateProbabilityDensityFunction> conjunctive, java.lang.Iterable<? extends ObservationType> data) Creates a new instance of ScalarEstimator

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

Classes in gov.sandia.cognition.statistics.bayesian.conjugate that implement BayesianParameter

Modifier and Type	Class and Description
static class	BernoulliBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	BinomialBayesianEstimator.Parameter Parameter of this relationship
static class	ExponentialBayesianEstimator.Parameter Bayesian parameter describing this conjugate relationship.
static class	GammaInverseScaleBayesianEstimator.Parameter Bayesian parameter describing this conjugate relationship.
static class	MultinomialBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	MultivariateGaussianMeanBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	MultivariateGaussianMeanCovarianceBayesianEstimator.Parameter Parameter for this conjugate prior estimator.
static class	PoissonBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	UniformDistributionBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	UnivariateGaussianMeanBayesianEstimator.Parameter Parameter of this conjugate prior relationship.
static class	UnivariateGaussianMeanVarianceBayesianEstimator.Parameter Parameter for this conjugate prior estimator.

Fields in gov.sandia.cognition.statistics.bayesian.conjugate declared as BayesianParameter

Modifier and Type	Field and Description
protected BayesianParameter<ParameterType,ConditionalType,BeliefType>	AbstractConjugatePriorBayesianEstimator.parameter Bayesian hyperparameter relationship between the conditional distribution and the conjugate prior distribution.

Methods in gov.sandia.cognition.statistics.bayesian.conjugate that return BayesianParameter

Modifier and Type	Method and Description
BayesianParameter<ParameterType,ConditionalType,BeliefType>	ConjugatePriorBayesianEstimator.createParameter(ConditionalType conditional, BeliefType prior) Creates a parameter linking the conditional and prior distributions
BayesianParameter<ParameterType,ConditionalType,BeliefType>	AbstractConjugatePriorBayesianEstimator.getParameter()
BayesianParameter<ParameterType,ConditionalType,BeliefType>	ConjugatePriorBayesianEstimator.getParameter() Gets the Bayesian hyperparameter relationship between the conditional distribution and the conjugate prior distribution.

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

Modifier and Type	Method and Description
protected void	AbstractConjugatePriorBayesianEstimator.setParameter(BayesianParameter<ParameterType,ConditionalType,BeliefType> parameter) Setter for parameter

Constructors in gov.sandia.cognition.statistics.bayesian.conjugate with parameters of type BayesianParameter

Constructor and Description
AbstractConjugatePriorBayesianEstimator(BayesianParameter<ParameterType,ConditionalType,BeliefType> parameter) Creates a new instance of AbstractConjugatePriorBayesianEstimator
BernoulliBayesianEstimator(BayesianParameter<java.lang.Double,BernoulliDistribution,BetaDistribution> parameter) Creates a new instance of BernoulliBayesianEstimator
BinomialBayesianEstimator(BayesianParameter<java.lang.Double,BinomialDistribution,BetaDistribution> parameter) Creates a new instance of BinomialBayesianEstimator
ExponentialBayesianEstimator(BayesianParameter<java.lang.Double,ExponentialDistribution,GammaDistribution> parameter) Creates a new instance of ExponentialBayesianEstimator
GammaInverseScaleBayesianEstimator(BayesianParameter<java.lang.Double,GammaDistribution,GammaDistribution> parameter) Creates a new instance of GammaInverseScaleBayesianEstimator
MultinomialBayesianEstimator(BayesianParameter<Vector,MultinomialDistribution,DirichletDistribution> parameter) Creates a new instance
MultivariateGaussianMeanBayesianEstimator(BayesianParameter<Vector,MultivariateGaussian,MultivariateGaussian> parameter) Creates a new instance
MultivariateGaussianMeanCovarianceBayesianEstimator(BayesianParameter<Matrix,MultivariateGaussian,NormalInverseWishartDistribution> parameter) Creates a new instance
PoissonBayesianEstimator(BayesianParameter<java.lang.Double,PoissonDistribution,GammaDistribution> parameter) Creates a new instance
UniformDistributionBayesianEstimator(BayesianParameter<java.lang.Double,UniformDistribution,ParetoDistribution> parameter) Creates a new instance
UnivariateGaussianMeanBayesianEstimator(BayesianParameter<java.lang.Double,UnivariateGaussian,UnivariateGaussian> parameter) Creates a new instance
UnivariateGaussianMeanVarianceBayesianEstimator(BayesianParameter<Vector,UnivariateGaussian,NormalInverseGammaDistribution> parameter) Creates a new instance of UnivariateGaussianMeanVarianceBayesianEstimator