random-fu-0.3.0.0: Random number generation
Safe HaskellNone
LanguageHaskell2010

Data.Random.Distribution.Gamma

Synopsis

Documentation

data Gamma a Source #

Constructors

Gamma a a 

Instances

Instances details
(Real a, Distribution Gamma a) => CDF Gamma a Source # 
Instance details

Defined in Data.Random.Distribution.Gamma

Methods

cdf :: Gamma a -> a -> Double Source #

(Floating a, Ord a, Distribution Normal a, Distribution StdUniform a) => Distribution Gamma a Source # 
Instance details

Defined in Data.Random.Distribution.Gamma

Methods

rvar :: Gamma a -> RVar a Source #

rvarT :: forall (n :: Type -> Type). Gamma a -> RVarT n a Source #

gamma :: Distribution Gamma a => a -> a -> RVar a Source #

gammaT :: Distribution Gamma a => a -> a -> RVarT m a Source #

newtype Erlang a b Source #

Constructors

Erlang a 

Instances

Instances details
(Integral a, Real b, Distribution (Erlang a) b) => CDF (Erlang a) b Source # 
Instance details

Defined in Data.Random.Distribution.Gamma

Methods

cdf :: Erlang a b -> b -> Double Source #

(Integral a, Floating b, Ord b, Distribution Normal b, Distribution StdUniform b) => Distribution (Erlang a) b Source # 
Instance details

Defined in Data.Random.Distribution.Gamma

Methods

rvar :: Erlang a b -> RVar b Source #

rvarT :: forall (n :: Type -> Type). Erlang a b -> RVarT n b Source #

erlang :: Distribution (Erlang a) b => a -> RVar b Source #

erlangT :: Distribution (Erlang a) b => a -> RVarT m b Source #

mtGamma :: (Floating a, Ord a, Distribution StdUniform a, Distribution Normal a) => a -> a -> RVarT m a Source #

derived from Marsaglia & Tang, "A Simple Method for generating gamma variables", ACM Transactions on Mathematical Software, Vol 26, No 3 (2000), p363-372.