statistics-0.16.2.1: A library of statistical types, data, and functions
Copyright(c) 2020 Ximin Luo
LicenseBSD3
Maintainerinfinity0@pwned.gg
Stabilityexperimental
Portabilityportable
Safe HaskellSafe-Inferred
LanguageHaskell2010

Statistics.Distribution.Lognormal

Contents

Description

The log normal distribution. This is a continuous probability distribution that describes data whose log is clustered around a mean. For example, the multiplicative product of many independent positive random variables.

Synopsis

Documentation

data LognormalDistribution Source #

The lognormal distribution.

Instances

Instances details
FromJSON LognormalDistribution Source # 
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Defined in Statistics.Distribution.Lognormal

ToJSON LognormalDistribution Source # 
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Data LognormalDistribution Source # 
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Methods

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

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

toConstr :: LognormalDistribution -> Constr #

dataTypeOf :: LognormalDistribution -> DataType #

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

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

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

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

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

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

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

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

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

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

Generic LognormalDistribution Source # 
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Defined in Statistics.Distribution.Lognormal

Associated Types

type Rep LognormalDistribution :: Type -> Type #

Read LognormalDistribution Source # 
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Show LognormalDistribution Source # 
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Binary LognormalDistribution Source # 
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Eq LognormalDistribution Source # 
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ContDistr LognormalDistribution Source # 
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ContGen LognormalDistribution Source # 
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Distribution LognormalDistribution Source # 
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Entropy LognormalDistribution Source # 
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MaybeEntropy LognormalDistribution Source # 
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MaybeMean LognormalDistribution Source # 
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MaybeVariance LognormalDistribution Source # 
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Mean LognormalDistribution Source # 
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Variance LognormalDistribution Source # 
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FromSample LognormalDistribution Double Source #

Variance is estimated using maximum likelihood method (biased estimation) over the log of the data.

Returns Nothing if sample contains less than one element or variance is zero (all elements are equal)

Instance details

Defined in Statistics.Distribution.Lognormal

type Rep LognormalDistribution Source # 
Instance details

Defined in Statistics.Distribution.Lognormal

type Rep LognormalDistribution = D1 ('MetaData "LognormalDistribution" "Statistics.Distribution.Lognormal" "statistics-0.16.2.1-3pqcJx3Latt5dz24Y5Wwoa" 'True) (C1 ('MetaCons "LND" 'PrefixI 'False) (S1 ('MetaSel ('Nothing :: Maybe Symbol) 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 NormalDistribution)))

Constructors

lognormalDistr Source #

Arguments

:: Double

Mu

-> Double

Sigma

-> LognormalDistribution 

Create log normal distribution from parameters.

lognormalDistrErr Source #

Create log normal distribution from parameters.

lognormalDistrMeanStddevErr Source #

Create log normal distribution from mean and standard deviation.

lognormalStandard :: LognormalDistribution Source #

Standard log normal distribution with mu 0 and sigma 1.

Mean is sqrt e and variance is (e - 1) * e.