statistics-0.16.2.1: 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 | Safe-Inferred
Language | Haskell2010

Statistics.Distribution.Lognormal

Contents

- Constructors

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

- data LognormalDistribution
- lognormalDistr :: Double -> Double -> LognormalDistribution
- lognormalDistrErr :: Double -> Double -> Either String LognormalDistribution
- lognormalDistrMeanStddevErr :: Double -> Double -> Either String LognormalDistribution
- lognormalStandard :: LognormalDistribution

# Documentation

data LognormalDistribution Source #

The lognormal distribution.

#### Instances

Instances details

FromJSON LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods parseJSON :: Value -> Parser LognormalDistribution Source # parseJSONList :: Value -> Parser [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 #
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 #

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 #
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 #
Binary LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods put :: LognormalDistribution -> Put Source # get :: Get LognormalDistribution Source # putList :: [LognormalDistribution] -> Put Source #
Eq LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods (==) :: LognormalDistribution -> LognormalDistribution -> Bool Source # (/=) :: LognormalDistribution -> LognormalDistribution -> Bool 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 #
ContGen LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods genContVar :: StatefulGen g m => LognormalDistribution -> g -> m Double Source #
Distribution LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods cumulative :: LognormalDistribution -> Double -> Double Source # complCumulative :: LognormalDistribution -> Double -> 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 #
MaybeMean LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods maybeMean :: LognormalDistribution -> Maybe 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 #
Variance LognormalDistribution Source # |
Instance details Defined in Statistics.Distribution.Lognormal Methods variance :: LognormalDistribution -> Double Source # stdDev :: LognormalDistribution -> 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-0.16.2.1-An1XEEv5tKOFj5G6JDoeTv" '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`.