Copyright	(c) 2011 Aleksey Khudyakov
License	BSD3
Maintainer	bos@serpentine.com
Stability	experimental
Portability	portable
Safe Haskell	Safe-Inferred
Language	Haskell2010

Statistics.Distribution.StudentT

Contents

Constructors
Accessors

Description

Student-T distribution

Synopsis

data StudentT
studentT :: Double -> StudentT
studentTE :: Double -> Maybe StudentT
studentTUnstandardized :: Double -> Double -> Double -> LinearTransform StudentT
studentTndf :: StudentT -> Double

Documentation

data StudentT Source #

Student-T distribution

Instances

Instances details

FromJSON StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods parseJSON :: Value -> Parser StudentT # parseJSONList :: Value -> Parser [StudentT] #
ToJSON StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods toJSON :: StudentT -> Value # toEncoding :: StudentT -> Encoding # toJSONList :: [StudentT] -> Value # toEncodingList :: [StudentT] -> Encoding #
Data StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods gfoldl :: (forall d b. Data d => c (d -> b) -> d -> c b) -> (forall g. g -> c g) -> StudentT -> c StudentT # gunfold :: (forall b r. Data b => c (b -> r) -> c r) -> (forall r. r -> c r) -> Constr -> c StudentT # toConstr :: StudentT -> Constr # dataTypeOf :: StudentT -> DataType # dataCast1 :: Typeable t => (forall d. Data d => c (t d)) -> Maybe (c StudentT) # dataCast2 :: Typeable t => (forall d e. (Data d, Data e) => c (t d e)) -> Maybe (c StudentT) # gmapT :: (forall b. Data b => b -> b) -> StudentT -> StudentT # gmapQl :: (r -> r' -> r) -> r -> (forall d. Data d => d -> r') -> StudentT -> r # gmapQr :: forall r r'. (r' -> r -> r) -> r -> (forall d. Data d => d -> r') -> StudentT -> r # gmapQ :: (forall d. Data d => d -> u) -> StudentT -> [u] # gmapQi :: Int -> (forall d. Data d => d -> u) -> StudentT -> u # gmapM :: Monad m => (forall d. Data d => d -> m d) -> StudentT -> m StudentT # gmapMp :: MonadPlus m => (forall d. Data d => d -> m d) -> StudentT -> m StudentT # gmapMo :: MonadPlus m => (forall d. Data d => d -> m d) -> StudentT -> m StudentT #
Generic StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Associated Types type Rep StudentT :: Type -> Type # Methods from :: StudentT -> Rep StudentT x # to :: Rep StudentT x -> StudentT #
Read StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods readsPrec :: Int -> ReadS StudentT # readList :: ReadS [StudentT] # readPrec :: ReadPrec StudentT # readListPrec :: ReadPrec [StudentT] #
Show StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods showsPrec :: Int -> StudentT -> ShowS # show :: StudentT -> String # showList :: [StudentT] -> ShowS #
Binary StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods put :: StudentT -> Put # get :: Get StudentT # putList :: [StudentT] -> Put #
Eq StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods (==) :: StudentT -> StudentT -> Bool # (/=) :: StudentT -> StudentT -> Bool #
ContDistr StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods density :: StudentT -> Double -> Double Source # logDensity :: StudentT -> Double -> Double Source # quantile :: StudentT -> Double -> Double Source # complQuantile :: StudentT -> Double -> Double Source #
ContGen StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods genContVar :: StatefulGen g m => StudentT -> g -> m Double Source #
Distribution StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods cumulative :: StudentT -> Double -> Double Source # complCumulative :: StudentT -> Double -> Double Source #
Entropy StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods entropy :: StudentT -> Double Source #
MaybeEntropy StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods maybeEntropy :: StudentT -> Maybe Double Source #
MaybeMean StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods maybeMean :: StudentT -> Maybe Double Source #
MaybeVariance StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT Methods maybeVariance :: StudentT -> Maybe Double Source # maybeStdDev :: StudentT -> Maybe Double Source #
type Rep StudentT Source #
Instance details Defined in Statistics.Distribution.StudentT type Rep StudentT = D1 ('MetaData "StudentT" "Statistics.Distribution.StudentT" "statistics-0.16.2.1-34qObKIlIVGJpKYv9daW0Y" 'True) (C1 ('MetaCons "StudentT" 'PrefixI 'True) (S1 ('MetaSel ('Just "studentTndf") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Double)))

Constructors

studentT :: Double -> StudentT Source #

Create Student-T distribution. Number of parameters must be positive.

studentTE :: Double -> Maybe StudentT Source #

Create Student-T distribution. Number of parameters must be positive.

studentTUnstandardized Source #

Arguments

:: Double	Number of degrees of freedom
-> Double	Central value (0 for standard Student T distribution)
-> Double	Scale parameter
-> LinearTransform StudentT

Create an unstandardized Student-t distribution.

Accessors

studentTndf :: StudentT -> Double Source #