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

Packages that use BayesianParameter
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
 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
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
 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
static
<ObservationType,ParameterType>
UnivariateGaussian
BayesianUtil.expectedDeviance(BayesianParameter<ParameterType,? extends ComputableDistribution<ObservationType>,?> predictiveDistribution, Iterable<? extends ObservationType> observations, 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>
ArrayList<ObservationType>
BayesianUtil.sample(BayesianParameter<ParameterType,? extends Distribution<ObservationType>,? extends Distribution<ParameterType>> parameter, 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
ImportanceSampling.DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive)
          Creates a new instance of DefaultUpdater
RejectionSampling.DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive)
          Creates a new instance of DefaultUpdater
RejectionSampling.DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive, Double scale, ProbabilityFunction<ParameterType> sampler)
          Creates a new instance of DefaultUpdater
RejectionSampling.DefaultUpdater(BayesianParameter<ParameterType,? extends ProbabilityFunction<ObservationType>,? extends ProbabilityFunction<ParameterType>> conjuctive, ProbabilityFunction<ParameterType> sampler)
          Creates a new instance of DefaultUpdater
RejectionSampling.ScalarEstimator(BayesianParameter<Double,? extends ProbabilityFunction<ObservationType>,? extends UnivariateProbabilityDensityFunction> conjunctive, 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
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
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
 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
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
AbstractConjugatePriorBayesianEstimator(BayesianParameter<ParameterType,ConditionalType,BeliefType> parameter)
          Creates a new instance of AbstractConjugatePriorBayesianEstimator
BernoulliBayesianEstimator(BayesianParameter<Double,BernoulliDistribution,BetaDistribution> parameter)
          Creates a new instance of BernoulliBayesianEstimator
BinomialBayesianEstimator(BayesianParameter<Double,BinomialDistribution,BetaDistribution> parameter)
          Creates a new instance of BinomialBayesianEstimator
ExponentialBayesianEstimator(BayesianParameter<Double,ExponentialDistribution,GammaDistribution> parameter)
          Creates a new instance of ExponentialBayesianEstimator
GammaInverseScaleBayesianEstimator(BayesianParameter<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<Double,PoissonDistribution,GammaDistribution> parameter)
          Creates a new instance
UniformDistributionBayesianEstimator(BayesianParameter<Double,UniformDistribution,ParetoDistribution> parameter)
          Creates a new instance
UnivariateGaussianMeanBayesianEstimator(BayesianParameter<Double,UnivariateGaussian,UnivariateGaussian> parameter)
          Creates a new instance
UnivariateGaussianMeanVarianceBayesianEstimator(BayesianParameter<Vector,UnivariateGaussian,NormalInverseGammaDistribution> parameter)
          Creates a new instance of UnivariateGaussianMeanVarianceBayesianEstimator