Uses of Class
gov.sandia.cognition.statistics.bayesian.AbstractMarkovChainMonteCarlo

Packages that use AbstractMarkovChainMonteCarlo
gov.sandia.cognition.statistics.bayesian Provides algorithms for computing Bayesian estimates of parameters. 
 

Uses of AbstractMarkovChainMonteCarlo in gov.sandia.cognition.statistics.bayesian
 

Subclasses of AbstractMarkovChainMonteCarlo in gov.sandia.cognition.statistics.bayesian
 class DirichletProcessMixtureModel<ObservationType>
          An implementation of Dirichlet Process clustering, which estimates the number of clusters and the centroids of the clusters from a set of data.
 class MetropolisHastingsAlgorithm<ObservationType,ParameterType>
          An implementation of the Metropolis-Hastings MCMC algorithm, which is the most general formulation of MCMC but can be slow.
 class ParallelDirichletProcessMixtureModel<ObservationType>
          A Parallelized version of vanilla Dirichlet Process Mixture Model learning.
 

Methods in gov.sandia.cognition.statistics.bayesian that return AbstractMarkovChainMonteCarlo
 AbstractMarkovChainMonteCarlo<ObservationType,ParameterType> AbstractMarkovChainMonteCarlo.clone()