| Package | Description |
|---|---|
| gov.sandia.cognition.statistics.bayesian |
Provides algorithms for computing Bayesian estimates of parameters.
|
| Modifier and Type | Class and Description |
|---|---|
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.
|
| Modifier and Type | Method and Description |
|---|---|
AbstractMarkovChainMonteCarlo<ObservationType,ParameterType> |
AbstractMarkovChainMonteCarlo.clone() |