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.Density.Free

Description

Density is a free monad transformer over random sampling.

Synopsis

data Density m a
hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> Density m a -> Density n a
interpret :: MonadDistribution m => Density m a -> m a
withRandomness :: Monad m => [Double] -> Density m a -> m a
density :: MonadDistribution m => [Double] -> Density m a -> m (a, [Double])
traced :: MonadDistribution m => [Double] -> Density Identity a -> m (a, [Double])

Documentation

data Density m a Source #

Free monad transformer over random sampling.

Uses the Church-encoded version of the free monad for efficiency.

Instances

Instances details

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

hoist :: (Monad m, Monad n) => (forall x. m x -> n x) -> Density m a -> Density n a Source #

Hoist Density through a monad transform.

interpret :: MonadDistribution m => Density m a -> m a Source #

Execute random sampling in the transformed monad.

withRandomness :: Monad m => [Double] -> Density m a -> m a Source #

Execute computation with supplied values for random choices.

density :: MonadDistribution m => [Double] -> Density m a -> m (a, [Double]) Source #

Execute computation with supplied values for a subset of random choices. Return the output value and a record of all random choices used, whether taken as input or drawn using the transformed monad.

traced :: MonadDistribution m => [Double] -> Density Identity a -> m (a, [Double]) Source #

Like density, but use an arbitrary sampling monad.