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 classAbstractHybridMCMCHybrid Monte Carlo, or Hamiltonian Monte Carlo, is a method that combines the traditional Metropolis algorithm, with molecular dynamics simulation.classHybridMCMCThis class implements a hybrid MCMC algorithm.classMultipointHybridMCMCA 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 classMetropolisThis basic Metropolis implementation assumes using symmetric proposal function.classMetropolisHastingsA generalization of the Metropolis algorithm, which allows asymmetric proposal functions.classRobustAdaptiveMetropolisA 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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