- Type Parameters:
ObservationType - Observations from the ConditionalType that are used to estimate the
parameters of the distribution.BeliefType - Type of Distribution that represents uncertainty in the parameters.ParameterType - Type of parameter estimated by this algorithm, which is used to
parameterize the conditional distribution.ConditionalType - Type of conditional distribution that generates observations for this
relationship.
- All Superinterfaces:
- BatchLearner<java.util.Collection<? extends ObservationType>,BeliefType>, BayesianEstimator<ObservationType,ParameterType,BeliefType>, BayesianEstimatorPredictor<ObservationType,ParameterType,BeliefType>, java.lang.Cloneable, CloneableSerializable, ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType,BeliefType>, IncrementalLearner<ObservationType,BeliefType>, RecursiveBayesianEstimator<ObservationType,ParameterType,BeliefType>, java.io.Serializable
- All Known Implementing Classes:
- BinomialBayesianEstimator, ExponentialBayesianEstimator, MultinomialBayesianEstimator, MultivariateGaussianMeanBayesianEstimator, MultivariateGaussianMeanCovarianceBayesianEstimator, PoissonBayesianEstimator, UnivariateGaussianMeanBayesianEstimator, UnivariateGaussianMeanVarianceBayesianEstimator
public interface ConjugatePriorBayesianEstimatorPredictor<ObservationType,ParameterType,ConditionalType extends ClosedFormDistribution<ObservationType>,BeliefType extends ClosedFormDistribution<ParameterType>>
extends ConjugatePriorBayesianEstimator<ObservationType,ParameterType,ConditionalType,BeliefType>, BayesianEstimatorPredictor<ObservationType,ParameterType,BeliefType>
A conjugate prior estimator that also has a closed-form predictive posterior.
- Since:
- 3.0
- Author:
- Kevin R. Dixon