| Copyright | (c) Adam Scibior 2015-2020 |
|---|---|
| License | MIT |
| Maintainer | leonhard.markert@tweag.io |
| Stability | experimental |
| Portability | GHC |
| Safe Haskell | None |
| Language | Haskell2010 |
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
- pmmh :: MonadInfer m => Int -> Int -> Int -> Traced m b -> (b -> Sequential (Population m) a) -> m [[(a, Log Double)]]
Documentation
Arguments
| :: MonadInfer m | |
| => Int | number of Metropolis-Hastings steps |
| -> Int | number of time steps |
| -> Int | number of particles |
| -> Traced m b | model parameters prior |
| -> (b -> Sequential (Population m) a) | model |
| -> m [[(a, Log Double)]] |
Particle Marginal Metropolis-Hastings sampling.