| Copyright | (c) Adam Scibior 2015-2020 |
|---|---|
| License | MIT |
| Maintainer | leonhard.markert@tweag.io |
| Stability | experimental |
| Portability | GHC |
| Safe Haskell | Safe-Inferred |
| Language | Haskell2010 |
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
- rmsmc :: MonadDistribution m => MCMCConfig -> SMCConfig m -> SequentialT (TracedT (PopulationT m)) a -> PopulationT m a
- rmsmcDynamic :: MonadDistribution m => MCMCConfig -> SMCConfig m -> SequentialT (TracedT (PopulationT m)) a -> PopulationT m a
- rmsmcBasic :: MonadDistribution m => MCMCConfig -> SMCConfig m -> SequentialT (TracedT (PopulationT m)) a -> PopulationT m a
Documentation
Arguments
| :: MonadDistribution m | |
| => MCMCConfig | |
| -> SMCConfig m | |
| -> SequentialT (TracedT (PopulationT m)) a | model |
| -> PopulationT m a |
Resample-move Sequential Monte Carlo.
Arguments
| :: MonadDistribution m | |
| => MCMCConfig | |
| -> SMCConfig m | |
| -> SequentialT (TracedT (PopulationT m)) a | model |
| -> PopulationT m a |
A variant of resample-move Sequential Monte Carlo where only random variables since last resampling are considered for rejuvenation.
Arguments
| :: MonadDistribution m | |
| => MCMCConfig | |
| -> SMCConfig m | |
| -> SequentialT (TracedT (PopulationT m)) a | model |
| -> PopulationT m a |
Resample-move Sequential Monte Carlo with a more efficient tracing representation.