Copyright	(c) 2009 Bryan O'Sullivan
License	BSD3
Maintainer	bos@serpentine.com
Stability	experimental
Portability	portable
Safe Haskell	None
Language	Haskell98

Statistics.Distribution.Normal

Contents

Constructors

Description

The normal distribution. This is a continuous probability distribution that describes data that cluster around a mean.

Synopsis

Documentation

data NormalDistribution Source #

The normal distribution.

Instances

Eq NormalDistribution Source #
Methods (==) :: NormalDistribution -> NormalDistribution -> Bool # (/=) :: NormalDistribution -> NormalDistribution -> Bool #
Data NormalDistribution Source #
Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> NormalDistribution -> c NormalDistribution # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c NormalDistribution # toConstr :: NormalDistribution -> Constr # dataTypeOf :: NormalDistribution -> DataType # dataCast1 :: Typeable (* -> ) t => (forall d. Data d => c (t d)) -> Maybe (c NormalDistribution) # dataCast2 :: Typeable ( -> * -> *) t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c NormalDistribution) # gmapT :: (forall b. Data b => b -> b) -> NormalDistribution -> NormalDistribution # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> NormalDistribution -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> NormalDistribution -> r # gmapQ :: (forall d. Data d => d -> u) -> NormalDistribution -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> NormalDistribution -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> NormalDistribution -> m NormalDistribution #
Read NormalDistribution Source #
Methods readsPrec :: Int -> ReadS NormalDistribution # readList :: ReadS [NormalDistribution] # readPrec :: ReadPrec NormalDistribution # readListPrec :: ReadPrec [NormalDistribution] #
Show NormalDistribution Source #
Methods showsPrec :: Int -> NormalDistribution -> ShowS # show :: NormalDistribution -> String # showList :: [NormalDistribution] -> ShowS #
Generic NormalDistribution Source #
Associated Types type Rep NormalDistribution :: * -> * # Methods from :: NormalDistribution -> Rep NormalDistribution x # to :: Rep NormalDistribution x -> NormalDistribution #
ToJSON NormalDistribution Source #
Methods toJSON :: NormalDistribution -> Value # toEncoding :: NormalDistribution -> Encoding # toJSONList :: [NormalDistribution] -> Value # toEncodingList :: [NormalDistribution] -> Encoding #
FromJSON NormalDistribution Source #
Methods parseJSON :: Value -> Parser NormalDistribution # parseJSONList :: Value -> Parser [NormalDistribution] #
Binary NormalDistribution Source #
Methods put :: NormalDistribution -> Put # get :: Get NormalDistribution # putList :: [NormalDistribution] -> Put #
ContGen NormalDistribution Source #
Methods genContVar :: PrimMonad m => NormalDistribution -> Gen (PrimState m) -> m Double Source #
Entropy NormalDistribution Source #
Methods entropy :: NormalDistribution -> Double Source #
MaybeEntropy NormalDistribution Source #
Methods maybeEntropy :: NormalDistribution -> Maybe Double Source #
Variance NormalDistribution Source #
Methods variance :: NormalDistribution -> Double Source # stdDev :: NormalDistribution -> Double Source #
MaybeVariance NormalDistribution Source #
Methods maybeVariance :: NormalDistribution -> Maybe Double Source # maybeStdDev :: NormalDistribution -> Maybe Double Source #
Mean NormalDistribution Source #
Methods mean :: NormalDistribution -> Double Source #
MaybeMean NormalDistribution Source #
Methods maybeMean :: NormalDistribution -> Maybe Double Source #
ContDistr NormalDistribution Source #
Methods density :: NormalDistribution -> Double -> Double Source # quantile :: NormalDistribution -> Double -> Double Source # complQuantile :: NormalDistribution -> Double -> Double Source # logDensity :: NormalDistribution -> Double -> Double Source #
Distribution NormalDistribution Source #
Methods cumulative :: NormalDistribution -> Double -> Double Source # complCumulative :: NormalDistribution -> Double -> Double Source #
FromSample NormalDistribution Double Source #	Variance is estimated using maximum likelihood method (biased estimation). Returns `Nothing` if sample contains less than one element or variance is zero (all elements are equal)
Methods fromSample :: Vector v Double => v Double -> Maybe NormalDistribution Source #
type Rep NormalDistribution Source #
type Rep NormalDistribution = D1 (MetaData "NormalDistribution" "Statistics.Distribution.Normal" "statistics-0.14.0.2-9wDz1lVU92ZDJSrAe5uHzb" False) (C1 (MetaCons "ND" PrefixI True) ((::) ((::) (S1 (MetaSel (Just Symbol "mean") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "stdDev") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double))) ((:*:) (S1 (MetaSel (Just Symbol "ndPdfDenom") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)) (S1 (MetaSel (Just Symbol "ndCdfDenom") SourceUnpack SourceStrict DecidedUnpack) (Rec0 Double)))))

Constructors

normalDistr Source #

Arguments

:: Double	Mean of distribution
-> Double	Standard deviation of distribution
-> NormalDistribution

Create normal distribution from parameters.

IMPORTANT: prior to 0.10 release second parameter was variance not standard deviation.

normalDistrE Source #

Arguments

:: Double	Mean of distribution
-> Double	Standard deviation of distribution
-> Maybe NormalDistribution

Create normal distribution from parameters.

IMPORTANT: prior to 0.10 release second parameter was variance not standard deviation.

standard :: NormalDistribution Source #

Standard normal distribution with mean equal to 0 and variance equal to 1