statistics-0.16.1.2: A library of statistical types, data, and functions
Copyright (c) 2020 Ximin Luo
License BSD3
Maintainer infinity0@pwned.gg
Stability experimental
Portability portable
Safe Haskell None
Language Haskell2010

Statistics.Distribution.Lognormal

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
Eq LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

(==) :: LognormalDistribution -> LognormalDistribution -> Bool Source #

(/=) :: LognormalDistribution -> LognormalDistribution -> Bool Source #

Data LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

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

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

toConstr :: LognormalDistribution -> Constr Source #

dataTypeOf :: LognormalDistribution -> DataType Source #

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

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

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

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

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

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

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

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

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

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

Read LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

readsPrec :: Int -> ReadS LognormalDistribution Source #

readList :: ReadS [ LognormalDistribution ] Source #

readPrec :: ReadPrec LognormalDistribution Source #

readListPrec :: ReadPrec [ LognormalDistribution ] Source #

Show LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

showsPrec :: Int -> LognormalDistribution -> ShowS Source #

show :: LognormalDistribution -> String Source #

showList :: [ LognormalDistribution ] -> ShowS Source #

Generic LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Associated Types

type Rep LognormalDistribution :: Type -> Type Source #

Methods

from :: LognormalDistribution -> Rep LognormalDistribution x Source #

to :: Rep LognormalDistribution x -> LognormalDistribution Source #

ToJSON LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

toJSON :: LognormalDistribution -> Value Source #

toEncoding :: LognormalDistribution -> Encoding Source #

toJSONList :: [ LognormalDistribution ] -> Value Source #

toEncodingList :: [ LognormalDistribution ] -> Encoding Source #

FromJSON LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

parseJSON :: Value -> Parser LognormalDistribution Source #

parseJSONList :: Value -> Parser [ LognormalDistribution ] Source #

Binary LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

put :: LognormalDistribution -> Put Source #

get :: Get LognormalDistribution Source #

putList :: [ LognormalDistribution ] -> Put Source #

ContGen LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

genContVar :: StatefulGen g m => LognormalDistribution -> g -> m Double Source #

Entropy LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

entropy :: LognormalDistribution -> Double Source #

MaybeEntropy LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

maybeEntropy :: LognormalDistribution -> Maybe Double Source #

Variance LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

variance :: LognormalDistribution -> Double Source #

stdDev :: LognormalDistribution -> Double Source #

MaybeVariance LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

maybeVariance :: LognormalDistribution -> Maybe Double Source #

maybeStdDev :: LognormalDistribution -> Maybe Double Source #

Mean LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

mean :: LognormalDistribution -> Double Source #

MaybeMean LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

maybeMean :: LognormalDistribution -> Maybe Double Source #

ContDistr LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

density :: LognormalDistribution -> Double -> Double Source #

logDensity :: LognormalDistribution -> Double -> Double Source #

quantile :: LognormalDistribution -> Double -> Double Source #

complQuantile :: LognormalDistribution -> Double -> Double Source #

Distribution LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

Methods

cumulative :: LognormalDistribution -> Double -> Double Source #

complCumulative :: LognormalDistribution -> Double -> Double Source #

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

Methods

fromSample :: Vector v Double => v Double -> Maybe LognormalDistribution Source #

type Rep LognormalDistribution Source #
Instance details

Defined in Statistics.Distribution.Lognormal

type Rep LognormalDistribution = D1 (' MetaData "LognormalDistribution" "Statistics.Distribution.Lognormal" "statistics-0.16.1.2-IkOne9g3oJ1vhHVSRLPUO" ' 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 #

Arguments

:: Double

Mu

-> Double

Sigma

-> Either String LognormalDistribution

Create log normal distribution from parameters.

lognormalDistrMeanStddevErr Source #

Arguments

:: Double

Mu

-> Double

Sigma

-> Either String LognormalDistribution

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 .