Copyright	(c) 2011 Aleksey Khudyakov
License	BSD3
Maintainer	bos@serpentine.com
Stability	experimental
Portability	portable
Safe Haskell	None
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] #

omittedField :: Maybe StudentT #

ToJSON StudentT Source #

Instance details

Defined in Statistics.Distribution.StudentT

Methods

toJSON :: StudentT -> Value #

toEncoding :: StudentT -> Encoding #

toJSONList :: [StudentT] -> Value #

toEncodingList :: [StudentT] -> Encoding #

omitField :: StudentT -> Bool #

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

Instance details

Defined in Statistics.Distribution.StudentT

type Rep StudentT = D1 ('MetaData "StudentT" "Statistics.Distribution.StudentT" "statistics-0.16.4.0-1cbrVsgEUI21RJju9YwBZG" 'True) (C1 ('MetaCons "StudentT" 'PrefixI 'True) (S1 ('MetaSel ('Just "studentTndf") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Double)))

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-0.16.4.0-1cbrVsgEUI21RJju9YwBZG" '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 #