Copyright	(c) 2010 Alexey Khudyakov
License	BSD3
Maintainer	bos@serpentine.com
Stability	experimental
Portability	portable
Safe Haskell	None
Language	Haskell2010

Statistics.Distribution.ChiSquared

Contents

Constructors

Description

The chi-squared distribution. This is a continuous probability distribution of sum of squares of k independent standard normal distributions. It's commonly used in statistical tests

Synopsis

Documentation

data ChiSquared Source #

Chi-squared distribution

Instances

Instances details

Eq ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods (==) :: ChiSquared -> ChiSquared -> Bool Source # (/=) :: ChiSquared -> ChiSquared -> Bool Source #
Data ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods gfoldl :: ( forall d b. Data d => c (d -> b) -> d -> c b) -> ( forall g. g -> c g) -> ChiSquared -> c ChiSquared Source # gunfold :: ( forall b r. Data b => c (b -> r) -> c r) -> ( forall r. r -> c r) -> Constr -> c ChiSquared Source # toConstr :: ChiSquared -> Constr Source # dataTypeOf :: ChiSquared -> DataType Source # dataCast1 :: Typeable t => ( forall d. Data d => c (t d)) -> Maybe (c ChiSquared ) Source # dataCast2 :: Typeable t => ( forall d e. ( Data d, Data e) => c (t d e)) -> Maybe (c ChiSquared ) Source # gmapT :: ( forall b. Data b => b -> b) -> ChiSquared -> ChiSquared Source # gmapQl :: (r -> r' -> r) -> r -> ( forall d. Data d => d -> r') -> ChiSquared -> r Source # gmapQr :: forall r r'. (r' -> r -> r) -> r -> ( forall d. Data d => d -> r') -> ChiSquared -> r Source # gmapQ :: ( forall d. Data d => d -> u) -> ChiSquared -> [u] Source # gmapQi :: Int -> ( forall d. Data d => d -> u) -> ChiSquared -> u Source # gmapM :: Monad m => ( forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source # gmapMp :: MonadPlus m => ( forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source # gmapMo :: MonadPlus m => ( forall d. Data d => d -> m d) -> ChiSquared -> m ChiSquared Source #
Read ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods readsPrec :: Int -> ReadS ChiSquared Source # readList :: ReadS [ ChiSquared ] Source # readPrec :: ReadPrec ChiSquared Source # readListPrec :: ReadPrec [ ChiSquared ] Source #
Show ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods showsPrec :: Int -> ChiSquared -> ShowS Source # show :: ChiSquared -> String Source # showList :: [ ChiSquared ] -> ShowS Source #
Generic ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Associated Types type Rep ChiSquared :: Type -> Type Source # Methods from :: ChiSquared -> Rep ChiSquared x Source # to :: Rep ChiSquared x -> ChiSquared Source #
ToJSON ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods toJSON :: ChiSquared -> Value Source # toEncoding :: ChiSquared -> Encoding Source # toJSONList :: [ ChiSquared ] -> Value Source # toEncodingList :: [ ChiSquared ] -> Encoding Source #
FromJSON ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods parseJSON :: Value -> Parser ChiSquared Source # parseJSONList :: Value -> Parser [ ChiSquared ] Source #
Binary ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods put :: ChiSquared -> Put Source # get :: Get ChiSquared Source # putList :: [ ChiSquared ] -> Put Source #
ContGen ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods genContVar :: StatefulGen g m => ChiSquared -> g -> m Double Source #
Entropy ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods entropy :: ChiSquared -> Double Source #
MaybeEntropy ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeEntropy :: ChiSquared -> Maybe Double Source #
Variance ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods variance :: ChiSquared -> Double Source # stdDev :: ChiSquared -> Double Source #
MaybeVariance ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeVariance :: ChiSquared -> Maybe Double Source # maybeStdDev :: ChiSquared -> Maybe Double Source #
Mean ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods mean :: ChiSquared -> Double Source #
MaybeMean ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeMean :: ChiSquared -> Maybe Double Source #
ContDistr ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods density :: ChiSquared -> Double -> Double Source # logDensity :: ChiSquared -> Double -> Double Source # quantile :: ChiSquared -> Double -> Double Source # complQuantile :: ChiSquared -> Double -> Double Source #
Distribution ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared Methods cumulative :: ChiSquared -> Double -> Double Source # complCumulative :: ChiSquared -> Double -> Double Source #
type Rep ChiSquared Source #
Instance details Defined in Statistics.Distribution.ChiSquared type Rep ChiSquared = D1 (' MetaData "ChiSquared" "Statistics.Distribution.ChiSquared" "statistics-0.16.1.2-IkOne9g3oJ1vhHVSRLPUO" ' True ) ( C1 (' MetaCons "ChiSquared" ' PrefixI ' True ) ( S1 (' MetaSel (' Just "chiSquaredNDF") ' NoSourceUnpackedness ' NoSourceStrictness ' DecidedLazy ) ( Rec0 Int )))

chiSquaredNDF :: ChiSquared -> Int Source #

Get number of degrees of freedom

Constructors

chiSquared :: Int -> ChiSquared Source #

Construct chi-squared distribution. Number of degrees of freedom must be positive.

chiSquaredE :: Int -> Maybe ChiSquared Source #

Construct chi-squared distribution. Number of degrees of freedom must be positive.