Package | Description |
---|---|
dev.nm.stat.random.rng.multivariate.mcmc.hybrid | |
dev.nm.stat.random.rng.multivariate.mcmc.metropolis |
Modifier and Type | Class and 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.
|
Modifier and Type | Class and 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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