Data.Random.Distribution.Discrete

Documentation

discrete :: Distribution (Discrete p) a => [(p, a)] -> RVar a

empirical :: (Num p, Ord a) => [a] -> Discrete p a

newtype Discrete p a

Constructors

Discrete [(p, a)]

Instances

Num p => Monad (Discrete p)

Functor (Discrete p)

Num p => Applicative (Discrete p)

Foldable (Discrete p)

Traversable (Discrete p)

(Num p, Ord p, Distribution Uniform p) => Distribution (Discrete p) a

(Eq p, Eq a) => Eq (Discrete p a)

(Show p, Show a) => Show (Discrete p a)

mapDiscreteWeights :: (p -> q) -> Discrete p e -> Discrete q e

Like fmap, but for the weights of a discrete distribution.

normalizeDiscreteWeights :: Fractional p => Discrete p e -> Discrete p e

Adjust all the weights of a discrete distribution so that they sum to unity. If not possible, returns the original distribution unchanged.

collectDiscreteEvents :: (Ord e, Num p, Ord p) => Discrete p e -> Discrete p e

Simplify a discrete distribution by combining equivalent events (the new event will have a weight equal to the sum of all the originals).

collectDiscreteEventsBy :: (e -> e -> Ordering) -> ([p] -> p) -> ([e] -> e) -> Discrete p e -> Discrete p e

Simplify a discrete distribution by combining equivalent events (the new event will have a weight equal to the sum of all the originals). The comparator function is used to identify events to combine. Once chosen, the events and their weights are combined (independently) by the provided weight and event aggregation functions.