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

Statistics.Distribution.Binomial

Contents

Constructors
Accessors

Description

The binomial distribution. This is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p.

Synopsis

data BinomialDistribution
binomial :: Int -> Double -> BinomialDistribution
binomialE :: Int -> Double -> Maybe BinomialDistribution
bdTrials :: BinomialDistribution -> Int
bdProbability :: BinomialDistribution -> Double

Documentation

data BinomialDistribution Source #

The binomial distribution.

Instances

Eq BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods (==) :: BinomialDistribution -> BinomialDistribution -> Bool # (/=) :: BinomialDistribution -> BinomialDistribution -> Bool #
Data BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> BinomialDistribution -> c BinomialDistribution # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c BinomialDistribution # toConstr :: BinomialDistribution -> Constr # dataTypeOf :: BinomialDistribution -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c BinomialDistribution) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c BinomialDistribution) # gmapT :: (forall b. Data b => b -> b) -> BinomialDistribution -> BinomialDistribution # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> BinomialDistribution -> r # gmapQr :: (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> BinomialDistribution -> r # gmapQ :: (forall d. Data d => d -> u) -> BinomialDistribution -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> BinomialDistribution -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> BinomialDistribution -> m BinomialDistribution # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> BinomialDistribution -> m BinomialDistribution # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> BinomialDistribution -> m BinomialDistribution #
Read BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods readsPrec :: Int -> ReadS BinomialDistribution # readList :: ReadS [BinomialDistribution] # readPrec :: ReadPrec BinomialDistribution # readListPrec :: ReadPrec [BinomialDistribution] #
Show BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods showsPrec :: Int -> BinomialDistribution -> ShowS # show :: BinomialDistribution -> String # showList :: [BinomialDistribution] -> ShowS #
Generic BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Associated Types type Rep BinomialDistribution :: Type -> Type # Methods from :: BinomialDistribution -> Rep BinomialDistribution x # to :: Rep BinomialDistribution x -> BinomialDistribution #
ToJSON BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods toJSON :: BinomialDistribution -> Value # toEncoding :: BinomialDistribution -> Encoding # toJSONList :: [BinomialDistribution] -> Value # toEncodingList :: [BinomialDistribution] -> Encoding #
FromJSON BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods parseJSON :: Value -> Parser BinomialDistribution # parseJSONList :: Value -> Parser [BinomialDistribution] #
Binary BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods put :: BinomialDistribution -> Put # get :: Get BinomialDistribution # putList :: [BinomialDistribution] -> Put #
Entropy BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods entropy :: BinomialDistribution -> Double Source #
MaybeEntropy BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods maybeEntropy :: BinomialDistribution -> Maybe Double Source #
Variance BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods variance :: BinomialDistribution -> Double Source # stdDev :: BinomialDistribution -> Double Source #
MaybeVariance BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods maybeVariance :: BinomialDistribution -> Maybe Double Source # maybeStdDev :: BinomialDistribution -> Maybe Double Source #
Mean BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods mean :: BinomialDistribution -> Double Source #
MaybeMean BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods maybeMean :: BinomialDistribution -> Maybe Double Source #
DiscreteDistr BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods probability :: BinomialDistribution -> Int -> Double Source # logProbability :: BinomialDistribution -> Int -> Double Source #
Distribution BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial Methods cumulative :: BinomialDistribution -> Double -> Double Source # complCumulative :: BinomialDistribution -> Double -> Double Source #
type Rep BinomialDistribution Source #
Instance details Defined in Statistics.Distribution.Binomial type Rep BinomialDistribution = D1 (MetaData "BinomialDistribution" "Statistics.Distribution.Binomial" "statistics-0.15.2.0-FCVAYbUNN6k6ys2hOZ1wTy" False) (C1 (MetaCons "BD" PrefixI True) (S1 (MetaSel (Just "bdTrials") SourceUnpack SourceStrict DecidedStrict) (Rec0 Int) :*: S1 (MetaSel (Just "bdProbability") SourceUnpack SourceStrict DecidedStrict) (Rec0 Double)))

Constructors

binomial Source #

Arguments

:: Int	Number of trials.
-> Double	Probability.
-> BinomialDistribution

Construct binomial distribution. Number of trials must be non-negative and probability must be in [0,1] range

binomialE Source #

Arguments

:: Int	Number of trials.
-> Double	Probability.
-> Maybe BinomialDistribution

Construct binomial distribution. Number of trials must be non-negative and probability must be in [0,1] range

Accessors

bdTrials :: BinomialDistribution -> Int Source #

Number of trials.

bdProbability :: BinomialDistribution -> Double Source #

Probability.