statistics-0.16.2.1: A library of statistical types, data, and functions
Copyright(c) 2011 Aleksey Khudyakov
LicenseBSD3
Maintainerbos@serpentine.com
Stabilityexperimental
Portabilityportable
Safe HaskellSafe-Inferred
LanguageHaskell2010

Statistics.Distribution.CauchyLorentz

Contents

Description

The Cauchy-Lorentz distribution. It's also known as Lorentz distribution or Breit–Wigner distribution.

It doesn't have mean and variance.

Synopsis

Documentation

data CauchyDistribution Source #

Cauchy-Lorentz distribution.

Instances

Instances details
FromJSON CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

ToJSON CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Data CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Methods

gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> CauchyDistribution -> c CauchyDistribution #

gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c CauchyDistribution #

toConstr :: CauchyDistribution -> Constr #

dataTypeOf :: CauchyDistribution -> DataType #

dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c CauchyDistribution) #

dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c CauchyDistribution) #

gmapT :: (forall b. Data b => b -> b) -> CauchyDistribution -> CauchyDistribution #

gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> CauchyDistribution -> r #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> CauchyDistribution -> r #

gmapQ :: (forall d. Data d => d -> u) -> CauchyDistribution -> [u] #

gmapQi :: Int -> (forall d. Data d => d -> u) -> CauchyDistribution -> u #

gmapM :: Monad m => (forall d. Data d => d -> m d) -> CauchyDistribution -> m CauchyDistribution #

gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> CauchyDistribution -> m CauchyDistribution #

gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> CauchyDistribution -> m CauchyDistribution #

Generic CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Associated Types

type Rep CauchyDistribution :: Type -> Type #

Read CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Show CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Binary CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Eq CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

ContDistr CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

ContGen CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Distribution CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

Entropy CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

MaybeEntropy CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

type Rep CauchyDistribution Source # 
Instance details

Defined in Statistics.Distribution.CauchyLorentz

type Rep CauchyDistribution = D1 ('MetaData "CauchyDistribution" "Statistics.Distribution.CauchyLorentz" "statistics-0.16.2.1-3pqcJx3Latt5dz24Y5Wwoa" 'False) (C1 ('MetaCons "CD" 'PrefixI 'True) (S1 ('MetaSel ('Just "cauchyDistribMedian") 'SourceUnpack 'SourceStrict 'DecidedStrict) (Rec0 Double) :*: S1 ('MetaSel ('Just "cauchyDistribScale") 'SourceUnpack 'SourceStrict 'DecidedStrict) (Rec0 Double)))

cauchyDistribMedian :: CauchyDistribution -> Double Source #

Central value of Cauchy-Lorentz distribution which is its mode and median. Distribution doesn't have mean so function is named after median.

cauchyDistribScale :: CauchyDistribution -> Double Source #

Scale parameter of Cauchy-Lorentz distribution. It's different from variance and specify half width at half maximum (HWHM).

Constructors

cauchyDistribution Source #

Arguments

:: Double

Central point

-> Double

Scale parameter (FWHM)

-> CauchyDistribution 

Cauchy distribution

cauchyDistributionE Source #

Arguments

:: Double

Central point

-> Double

Scale parameter (FWHM)

-> Maybe CauchyDistribution 

Cauchy distribution

standardCauchy :: CauchyDistribution Source #

Standard Cauchy distribution. It's centered at 0 and have 1 FWHM