Control.Monad.Bayes.Traced.Static

Documentation

data TracedT m a

A tracing monad where only a subset of random choices are traced.

The random choices that are not to be traced should be lifted from the transformed monad.

Constructors

TracedT

Fields

• model :: WeightedT (DensityT m) a
• traceDist :: m (Trace a)

Instances

MonadTrans TracedT

Defined in Control.Monad.Bayes.Traced.Static

Methods

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

Monad m => Applicative (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

Methods

pure :: a -> TracedT m a

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

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

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

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

Monad m => Functor (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

Methods

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

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

Monad m => Monad (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

Methods

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

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

return :: a -> TracedT m a

MonadDistribution m => MonadDistribution (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

Methods

random :: TracedT m Double

uniform :: Double -> Double -> TracedT m Double

normal :: Double -> Double -> TracedT m Double

gamma :: Double -> Double -> TracedT m Double

beta :: Double -> Double -> TracedT m Double

bernoulli :: Double -> TracedT m Bool

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

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

uniformD :: [a] -> TracedT m a

geometric :: Double -> TracedT m Int

poisson :: Double -> TracedT m Int

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

MonadFactor m => MonadFactor (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

Methods

score :: Log Double -> TracedT m ()

MonadMeasure m => MonadMeasure (TracedT m)

Defined in Control.Monad.Bayes.Traced.Static

hoist :: (forall x. m x -> m x) -> TracedT m a -> TracedT m a

marginal :: Monad m => TracedT m a -> m a

Discard the trace and supporting infrastructure.

mhStep :: MonadDistribution m => TracedT m a -> TracedT m a

A single step of the Trace Metropolis-Hastings algorithm.

mh :: MonadDistribution m => Int -> TracedT m a -> m [a]

Full run of the Trace Metropolis-Hastings algorithm with a specified number of steps. Newest samples are at the head of the list.

For example:

• I have forgotten what day it is.
• There are ten buses per hour in the week and three buses per hour at the weekend.
• I observe four buses in a given hour.
• What is the probability that it is the weekend?

>>> :{
 let
   bus = do x <- bernoulli (2/7)
            let rate = if x then 3 else 10
            factor $ poissonPdf rate 4
            return x
   mhRunBusSingleObs = do
     let nSamples = 2
     sampleIOfixed $ unweighted $ mh nSamples bus
 in mhRunBusSingleObs
:}
[True,True,True]

Of course, it will need to be run more than twice to get a reasonable estimate.