monad-bayes-1.3.0.1: A library for probabilistic programming.
Copyright(c) Adam Scibior 2015-2020
LicenseMIT
Maintainerleonhard.markert@tweag.io
Stabilityexperimental
PortabilityGHC
Safe HaskellSafe-Inferred
LanguageHaskell2010

Control.Monad.Bayes.Inference.PMMH

Description

Particle Marginal Metropolis-Hastings (PMMH) sampling.

Christophe Andrieu, Arnaud Doucet, and Roman Holenstein. 2010. Particle Markov chain Monte Carlo Methods. Journal of the Royal Statistical Society 72 (2010), 269-342. http://www.stats.ox.ac.uk/~doucet/andrieu_doucet_holenstein_PMCMC.pdf

Synopsis

Documentation

pmmh :: MonadDistribution m => MCMCConfig -> SMCConfig (WeightedT m) -> TracedT (WeightedT m) a1 -> (a1 -> SequentialT (PopulationT (WeightedT m)) a2) -> m [[(a2, Log Double)]] Source #

Particle Marginal Metropolis-Hastings sampling.

pmmhBayesianModel :: MonadMeasure m => MCMCConfig -> SMCConfig (WeightedT m) -> (forall m'. MonadMeasure m' => Bayesian m' a1 a2) -> m [[(a2, Log Double)]] Source #

Particle Marginal Metropolis-Hastings sampling from a Bayesian model