gov.sandia.cognition.statistics.bayesian
Interface RecursiveBayesianEstimator<ObservationType,ParameterType,BeliefType extends Distribution<ParameterType>>

Type Parameters:
ObservationType - Type of observations incorporated by the model
ParameterType - Type of parameter that we are estimating
BeliefType - Belief distribution of the parameter
All Superinterfaces:
BatchLearner<Collection<? extends ObservationType>,BeliefType>, BayesianEstimator<ObservationType,ParameterType,BeliefType>, Cloneable, CloneableSerializable, IncrementalLearner<ObservationType,BeliefType>, Serializable
All Known Subinterfaces:
ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType,BeliefType>, ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType,BeliefType>, ParticleFilter<ObservationType,ParameterType>
All Known Implementing Classes:
AbstractConjugatePriorBayesianEstimator, AbstractKalmanFilter, AbstractParticleFilter, BernoulliBayesianEstimator, BinomialBayesianEstimator, ExponentialBayesianEstimator, ExtendedKalmanFilter, GammaInverseScaleBayesianEstimator, KalmanFilter, MultinomialBayesianEstimator, MultivariateGaussianMeanBayesianEstimator, MultivariateGaussianMeanCovarianceBayesianEstimator, PoissonBayesianEstimator, SamplingImportanceResamplingParticleFilter, UniformDistributionBayesianEstimator, UnivariateGaussianMeanBayesianEstimator, UnivariateGaussianMeanVarianceBayesianEstimator

@PublicationReference(author="Wikipedia",
                      title="Recursive Bayesian estimation",
                      type=WebPage,
                      year=2010,
                      url="http://en.wikipedia.org/wiki/Recursive_Bayesian_estimation")
public interface RecursiveBayesianEstimator<ObservationType,ParameterType,BeliefType extends Distribution<ParameterType>>
extends BayesianEstimator<ObservationType,ParameterType,BeliefType>, IncrementalLearner<ObservationType,BeliefType>

A recursive Bayesian estimator is an estimation method that uses the previous belief of the system parameter and a single observation to refine the estimate of the system parameter.

Since:
3.0
Author:
Kevin R. Dixon

Method Summary
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.BatchLearner
learn
 
Methods inherited from interface gov.sandia.cognition.util.CloneableSerializable
clone
 
Methods inherited from interface gov.sandia.cognition.learning.algorithm.IncrementalLearner
createInitialLearnedObject, update, update