Uses of Class
dev.nm.stat.random.rng.multivariate.mcmc.metropolis.AbstractMetropolis
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Packages that use AbstractMetropolis Package Description dev.nm.stat.random.rng.multivariate.mcmc.hybrid dev.nm.stat.random.rng.multivariate.mcmc.metropolis -
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Uses of AbstractMetropolis in dev.nm.stat.random.rng.multivariate.mcmc.hybrid
Subclasses of AbstractMetropolis in dev.nm.stat.random.rng.multivariate.mcmc.hybrid Modifier and Type Class Description class
AbstractHybridMCMC
Hybrid Monte Carlo, or Hamiltonian Monte Carlo, is a method that combines the traditional Metropolis algorithm, with molecular dynamics simulation.class
HybridMCMC
This class implements a hybrid MCMC algorithm.class
MultipointHybridMCMC
A multi-point Hybrid Monte Carlo is an extension of HybridMCMC, where during the proposal generation instead of considering only the last configuration after the dynamics simulation, we pick a proposal from a window of the last M configurations. -
Uses of AbstractMetropolis in dev.nm.stat.random.rng.multivariate.mcmc.metropolis
Subclasses of AbstractMetropolis in dev.nm.stat.random.rng.multivariate.mcmc.metropolis Modifier and Type Class Description class
Metropolis
This basic Metropolis implementation assumes using symmetric proposal function.class
MetropolisHastings
A generalization of the Metropolis algorithm, which allows asymmetric proposal functions.class
RobustAdaptiveMetropolis
A variation of Metropolis, that uses the estimated covariance of the target distribution in the proposal distribution, based on a paper by Vihola (2011).
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