monad-bayes-0.1.0.0: A library for probabilistic programming.

Copyright(c) Adam Scibior 2015-2020
LicenseMIT
Maintainerleonhard.markert@tweag.io
Stabilityexperimental
PortabilityGHC
Safe HaskellNone
LanguageHaskell2010

Control.Monad.Bayes.Inference.RMSMC

Description

Resample-move Sequential Monte Carlo (RM-SMC) sampling.

Walter Gilks and Carlo Berzuini. 2001. Following a moving target - Monte Carlo inference for dynamic Bayesian models. Journal of the Royal Statistical Society 63 (2001), 127-146. http://www.mathcs.emory.edu/~whalen/Papers/BNs/MonteCarlo-DBNs.pdf

Synopsis

Documentation

rmsmc Source #

Arguments

:: MonadSample m 
=> Int

number of timesteps

-> Int

number of particles

-> Int

number of Metropolis-Hastings transitions after each resampling

-> Sequential (Traced (Population m)) a

model

-> Population m a 

Resample-move Sequential Monte Carlo.

rmsmcLocal Source #

Arguments

:: MonadSample m 
=> Int

number of timesteps

-> Int

number of particles

-> Int

number of Metropolis-Hastings transitions after each resampling

-> Sequential (Traced (Population m)) a

model

-> Population m a 

A variant of resample-move Sequential Monte Carlo where only random variables since last resampling are considered for rejuvenation.

rmsmcBasic Source #

Arguments

:: MonadSample m 
=> Int

number of timesteps

-> Int

number of particles

-> Int

number of Metropolis-Hastings transitions after each resampling

-> Sequential (Traced (Population m)) a

model

-> Population m a 

Resample-move Sequential Monte Carlo with a more efficient tracing representation.