Uses of Interface

Packages that use RecursiveBayesianEstimator
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 RecursiveBayesianEstimator in gov.sandia.cognition.statistics.bayesian

Subinterfaces of RecursiveBayesianEstimator in gov.sandia.cognition.statistics.bayesian
 interface ParticleFilter<ObservationType,ParameterType>
          A particle filter aims to estimate a sequence of hidden parameters based on observed data using point-mass estimates of the posterior distribution.

Classes in gov.sandia.cognition.statistics.bayesian that implement RecursiveBayesianEstimator
 class AbstractKalmanFilter
          Contains fields useful to both Kalman filters and extended Kalman filters.
 class AbstractParticleFilter<ObservationType,ParameterType>
          Partial abstract implementation of ParticleFilter.
 class ExtendedKalmanFilter
          Implements the Extended Kalman Filter (EKF), which is an extension of the Kalman filter that allows nonlinear motion and observation models.
 class KalmanFilter
          A Kalman filter estimates the state of a dynamical system corrupted with white Gaussian noise with observations that are corrupted with white Gaussian noise.
 class SamplingImportanceResamplingParticleFilter<ObservationType,ParameterType>
          An implementation of the standard Sampling Importance Resampling particle filter.

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

Subinterfaces of RecursiveBayesianEstimator in gov.sandia.cognition.statistics.bayesian.conjugate
 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.

Classes in gov.sandia.cognition.statistics.bayesian.conjugate that implement RecursiveBayesianEstimator
 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 BernoulliBayesianEstimator
          A Bayesian estimator for the parameter of a BernoulliDistribution using the conjugate prior BetaDistribution.
 class BinomialBayesianEstimator
          A Bayesian estimator for the parameter of a Bernoulli parameter, p, of a BinomialDistribution using the conjugate prior BetaDistribution.
 class ExponentialBayesianEstimator
          Conjugate prior Bayesian estimator of the "rate" parameter of an Exponential distribution using the conjugate prior Gamma distribution.
 class GammaInverseScaleBayesianEstimator
          A Bayesian estimator for the scale parameter of a Gamma distribution using the conjugate prior Gamma distribution for the inverse-scale (rate) of the Gamma.
 class MultinomialBayesianEstimator
          A Bayesian estimator for the parameters of a MultinomialDistribution using its conjugate prior distribution, the DirichletDistribution.
 class MultivariateGaussianMeanBayesianEstimator
          Bayesian estimator for the mean of a MultivariateGaussian using its conjugate prior, which is also a MultivariateGaussian.
 class MultivariateGaussianMeanCovarianceBayesianEstimator
          Performs robust estimation of both the mean and covariance of a MultivariateGaussian conditional distribution using the conjugate prior Normal-Inverse-Wishart distribution.
 class PoissonBayesianEstimator
          A Bayesian estimator for the parameter of a PoissonDistribution using the conjugate prior GammaDistribution.
 class UniformDistributionBayesianEstimator
          A Bayesian estimator for a conditional Uniform(0,theta) distribution using its conjugate prior Pareto distribution.
 class UnivariateGaussianMeanBayesianEstimator
          Bayesian estimator for the mean of a UnivariateGaussian using its conjugate prior, which is also a UnivariateGaussian.
 class UnivariateGaussianMeanVarianceBayesianEstimator
          Computes the mean and variance of a univariate Gaussian using the conjugate prior NormalInverseGammaDistribution