/*
* File: BayesianEstimatorPredictor.java
* Authors: Kevin R. Dixon
* Company: Sandia National Laboratories
* Project: Cognitive Foundry
*
* Copyright Mar 23, 2010, Sandia Corporation.
* Under the terms of Contract DE-AC04-94AL85000, there is a non-exclusive
* license for use of this work by or on behalf of the U.S. Government.
* Export of this program may require a license from the United States
* Government. See CopyrightHistory.txt for complete details.
*
*/
package gov.sandia.cognition.statistics.bayesian;
import gov.sandia.cognition.statistics.ComputableDistribution;
import gov.sandia.cognition.statistics.Distribution;
/**
* A BayesianEstimator that can also compute the predictive distribution of
* new data given the posterior.
* @author Kevin R. Dixon
* @since 3.0
* @param <ObservationType>
* Observations from the ConditionalType that are used to estimate the
* parameters of the distribution.
* @param <ParameterType>
* Type of parameter estimated by this algorithm, which is used to
* parameterize the conditional distribution.
* @param <PosteriorType>
* Type of posterior Distribution, which describes the uncertainty of the
* parameters after we have incorporated the observations.
*/
public interface BayesianEstimatorPredictor<ObservationType, ParameterType,
PosteriorType extends Distribution<? extends ParameterType>>
extends BayesianEstimator<ObservationType,ParameterType,PosteriorType>
{
/**
* Creates the predictive distribution of new data given the posterior.
* This is equivalent to evaluating the integral of:
* p( newdata | data ) = integral( conditional( newdata | data, parameters ) * p( parameters | data ) dparameters )
* @param posterior
* Posterior distribution from which to compute the predictive posterior.
* @return
* Predictive distribution of new data given the observed data.
*/
public ComputableDistribution<ObservationType> createPredictiveDistribution(
PosteriorType posterior );
}