Control.Monad.Bayes.Weighted

Weighted is an instance of MonadFactor. Apply a MonadDistribution transformer to obtain a MonadMeasure that can execute probabilistic models.

Documentation

data Weighted m a

Execute the program using the prior distribution, while accumulating likelihood.

Instances

MonadTrans Weighted

Defined in Control.Monad.Bayes.Weighted

Methods

lift :: Monad m => m a -> Weighted m a

MonadIO m => MonadIO (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

liftIO :: IO a -> Weighted m a

Monad m => Applicative (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

pure :: a -> Weighted m a

(<*>) :: Weighted m (a -> b) -> Weighted m a -> Weighted m b

liftA2 :: (a -> b -> c) -> Weighted m a -> Weighted m b -> Weighted m c

(*>) :: Weighted m a -> Weighted m b -> Weighted m b

(<*) :: Weighted m a -> Weighted m b -> Weighted m a

Functor m => Functor (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

fmap :: (a -> b) -> Weighted m a -> Weighted m b

(<$) :: a -> Weighted m b -> Weighted m a

Monad m => Monad (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

(>>=) :: Weighted m a -> (a -> Weighted m b) -> Weighted m b

(>>) :: Weighted m a -> Weighted m b -> Weighted m b

return :: a -> Weighted m a

MonadDistribution m => MonadDistribution (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

random :: Weighted m Double

uniform :: Double -> Double -> Weighted m Double

normal :: Double -> Double -> Weighted m Double

gamma :: Double -> Double -> Weighted m Double

beta :: Double -> Double -> Weighted m Double

bernoulli :: Double -> Weighted m Bool

categorical :: Vector v Double => v Double -> Weighted m Int

logCategorical :: (Vector v (Log Double), Vector v Double) => v (Log Double) -> Weighted m Int

uniformD :: [a] -> Weighted m a

geometric :: Double -> Weighted m Int

poisson :: Double -> Weighted m Int

dirichlet :: Vector v Double => v Double -> Weighted m (v Double)

Monad m => MonadFactor (Weighted m)

Defined in Control.Monad.Bayes.Weighted

Methods

score :: Log Double -> Weighted m ()

MonadDistribution m => MonadMeasure (Weighted m)

Defined in Control.Monad.Bayes.Weighted

withWeight :: Monad m => m (a, Log Double) -> Weighted m a

Embed a random variable with explicitly given likelihood.

weighted . withWeight = id

weighted :: Weighted m a -> m (a, Log Double)

Obtain an explicit value of the likelihood for a given value.

extractWeight :: Functor m => Weighted m a -> m (Log Double)

Compute the weight and discard the sample.

unweighted :: Functor m => Weighted m a -> m a

Compute the sample and discard the weight.

This operation introduces bias.

applyWeight :: MonadFactor m => Weighted m a -> m a

Use the weight as a factor in the transformed monad.

hoist :: (forall x. m x -> n x) -> Weighted m a -> Weighted n a

Apply a transformation to the transformed monad.

runWeighted :: Weighted m a -> m (a, Log Double)

Obtain an explicit value of the likelihood for a given value.