random-fu-0.3.0.1: Random number generation

Safe Haskell | None
Language | Haskell2010

Data.Random.Distribution.Exponential

Synopsis

- newtype Exponential a = Exp a
- floatingExponential :: forall a (m :: Type -> Type). (Floating a, Distribution StdUniform a) => a -> RVarT m a
- floatingExponentialCDF :: Real a => a -> a -> Double
- exponential :: Distribution Exponential a => a -> RVar a
- exponentialT :: forall a (m :: Type -> Type). Distribution Exponential a => a -> RVarT m a

# Documentation

newtype Exponential a Source #

A definition of the exponential distribution over the type `a`.

``Exp` mu` models an exponential distribution with mean `mu`. This can alternatively be viewed as an exponential distribution with parameter `lambda = 1 / mu`.

See also `exponential`.

Constructors

Exp a |

#### Instances

Instances details

(Real a, Distribution Exponential a) => CDF Exponential a Source # |
Instance details Defined in Data.Random.Distribution.Exponential Methods cdf :: Exponential a -> a -> Double Source #
(Floating a, Distribution StdUniform a) => Distribution Exponential a Source # |
Instance details Defined in Data.Random.Distribution.Exponential Methods rvar :: Exponential a -> RVar a Source # rvarT :: forall (n :: Type -> Type). Exponential a -> RVarT n a Source #

floatingExponential :: forall a (m :: Type -> Type). (Floating a, Distribution StdUniform a) => a -> RVarT m a Source #

floatingExponentialCDF :: Real a => a -> a -> Double Source #

exponential :: Distribution Exponential a => a -> RVar a Source #

A random variable which samples from the exponential distribution.

``exponential` mu` is an exponential random variable with mean `mu`. This can alternatively be viewed as an exponential random variable with parameter `lambda = 1 / mu`.

exponentialT :: forall a (m :: Type -> Type). Distribution Exponential a => a -> RVarT m a Source #

A random variable transformer which samples from the exponential distribution.

``exponentialT` mu` is an exponential random variable with mean `mu`. This can alternatively be viewed as an exponential random variable with parameter `lambda = 1 / mu`.