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.SMC2

Description

Sequential Monte Carlo squared (SMC²) sampling.

Nicolas Chopin, Pierre E. Jacob, and Omiros Papaspiliopoulos. 2013. SMC²: an efficient algorithm for sequential analysis of state space models. Journal of the Royal Statistical Society Series B: Statistical Methodology 75 (2013), 397-426. Issue 3. https://doi.org/10.1111/j.1467-9868.2012.01046.x

Synopsis

smc2 :: MonadDistribution m => Int -> Int -> Int -> Int -> SequentialT (TracedT (PopulationT m)) b -> (b -> SequentialT (PopulationT (SMC2 m)) a) -> PopulationT m [(a, Log Double)]
data SMC2 m a

Documentation

smc2 Source #

Arguments

:: MonadDistribution m
=> Int	number of time steps
-> Int	number of inner particles
-> Int	number of outer particles
-> Int	number of MH transitions
-> SequentialT (TracedT (PopulationT m)) b	model parameters
-> (b -> SequentialT (PopulationT (SMC2 m)) a)	model
-> PopulationT m [(a, Log Double)]

Sequential Monte Carlo squared.

data SMC2 m a Source #

Helper monad transformer for preprocessing the model for smc2.

Instances

Instances details

MonadTrans SMC2 Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods lift :: Monad m => m a -> SMC2 m a #
Monad m => Applicative (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods pure :: a -> SMC2 m a # (<>) :: SMC2 m (a -> b) -> SMC2 m a -> SMC2 m b # liftA2 :: (a -> b -> c) -> SMC2 m a -> SMC2 m b -> SMC2 m c # (>) :: SMC2 m a -> SMC2 m b -> SMC2 m b # (<*) :: SMC2 m a -> SMC2 m b -> SMC2 m a #
Monad m => Functor (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods fmap :: (a -> b) -> SMC2 m a -> SMC2 m b # (<$) :: a -> SMC2 m b -> SMC2 m a #
Monad m => Monad (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods (>>=) :: SMC2 m a -> (a -> SMC2 m b) -> SMC2 m b # (>>) :: SMC2 m a -> SMC2 m b -> SMC2 m b # return :: a -> SMC2 m a #
MonadDistribution m => MonadDistribution (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods random :: SMC2 m Double Source # uniform :: Double -> Double -> SMC2 m Double Source # normal :: Double -> Double -> SMC2 m Double Source # gamma :: Double -> Double -> SMC2 m Double Source # beta :: Double -> Double -> SMC2 m Double Source # bernoulli :: Double -> SMC2 m Bool Source # categorical :: Vector v Double => v Double -> SMC2 m Int Source # logCategorical :: (Vector v (Log Double), Vector v Double) => v (Log Double) -> SMC2 m Int Source # uniformD :: [a] -> SMC2 m a Source # geometric :: Double -> SMC2 m Int Source # poisson :: Double -> SMC2 m Int Source # dirichlet :: Vector v Double => v Double -> SMC2 m (v Double) Source #
Monad m => MonadFactor (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2 Methods score :: Log Double -> SMC2 m () Source #
MonadDistribution m => MonadMeasure (SMC2 m) Source #
Instance details Defined in Control.Monad.Bayes.Inference.SMC2