statistics-0.15.0.0: A library of statistical types, data, and functions

Statistics.Distribution.Normal

Contents

Description

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

Synopsis

# Documentation

The normal distribution.

Instances
 Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methodsgfoldl :: (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 #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 # Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal MethodsshowList :: [NormalDistribution] -> ShowS # Source # Instance detailsDefined in Statistics.Distribution.Normal Associated Typestype Rep NormalDistribution :: * -> * # Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal MethodsputList :: [NormalDistribution] -> Put # Source # Instance detailsDefined in Statistics.Distribution.Normal MethodsgenContVar :: PrimMonad m => NormalDistribution -> Gen (PrimState m) -> m Double Source # Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal Methods 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) Instance detailsDefined in Statistics.Distribution.Normal Methods Source # Instance detailsDefined in Statistics.Distribution.Normal type Rep NormalDistribution = D1 (MetaData "NormalDistribution" "Statistics.Distribution.Normal" "statistics-0.15.0.0-AkglZgHZAgx3cdskkvnxTn" False) (C1 (MetaCons "ND" PrefixI True) ((S1 (MetaSel (Just "mean") SourceUnpack SourceStrict DecidedStrict) (Rec0 Double) :*: S1 (MetaSel (Just "stdDev") SourceUnpack SourceStrict DecidedStrict) (Rec0 Double)) :*: (S1 (MetaSel (Just "ndPdfDenom") SourceUnpack SourceStrict DecidedStrict) (Rec0 Double) :*: S1 (MetaSel (Just "ndCdfDenom") SourceUnpack SourceStrict DecidedStrict) (Rec0 Double))))

# Constructors

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.

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