statistics-0.16.1.2: A library of statistical types, data, and functions
Copyright (c) 2011 Aleksey Khudyakov
License BSD3
Maintainer bos@serpentine.com
Stability experimental
Portability portable
Safe Haskell None
Language Haskell2010

Statistics.Distribution.StudentT

Description

Student-T distribution

Synopsis

Documentation

data StudentT Source #

Student-T distribution

Instances

Instances details
Eq StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

(==) :: StudentT -> StudentT -> Bool Source #

(/=) :: StudentT -> StudentT -> Bool Source #

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 Source #

gunfold :: ( forall b r. Data b => c (b -> r) -> c r) -> ( forall r. r -> c r) -> Constr -> c StudentT Source #

toConstr :: StudentT -> Constr Source #

dataTypeOf :: StudentT -> DataType Source #

dataCast1 :: Typeable t => ( forall d. Data d => c (t d)) -> Maybe (c StudentT ) Source #

dataCast2 :: Typeable t => ( forall d e. ( Data d, Data e) => c (t d e)) -> Maybe (c StudentT ) Source #

gmapT :: ( forall b. Data b => b -> b) -> StudentT -> StudentT Source #

gmapQl :: (r -> r' -> r) -> r -> ( forall d. Data d => d -> r') -> StudentT -> r Source #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> ( forall d. Data d => d -> r') -> StudentT -> r Source #

gmapQ :: ( forall d. Data d => d -> u) -> StudentT -> [u] Source #

gmapQi :: Int -> ( forall d. Data d => d -> u) -> StudentT -> u Source #

gmapM :: Monad m => ( forall d. Data d => d -> m d) -> StudentT -> m StudentT Source #

gmapMp :: MonadPlus m => ( forall d. Data d => d -> m d) -> StudentT -> m StudentT Source #

gmapMo :: MonadPlus m => ( forall d. Data d => d -> m d) -> StudentT -> m StudentT Source #

Read StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

readsPrec :: Int -> ReadS StudentT Source #

readList :: ReadS [ StudentT ] Source #

readPrec :: ReadPrec StudentT Source #

readListPrec :: ReadPrec [ StudentT ] Source #

Show StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

showsPrec :: Int -> StudentT -> ShowS Source #

show :: StudentT -> String Source #

showList :: [ StudentT ] -> ShowS Source #

Generic StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Associated Types

type Rep StudentT :: Type -> Type Source #

Methods

from :: StudentT -> Rep StudentT x Source #

to :: Rep StudentT x -> StudentT Source #

ToJSON StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

toJSON :: StudentT -> Value Source #

toEncoding :: StudentT -> Encoding Source #

toJSONList :: [ StudentT ] -> Value Source #

toEncodingList :: [ StudentT ] -> Encoding Source #

FromJSON StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

parseJSON :: Value -> Parser StudentT Source #

parseJSONList :: Value -> Parser [ StudentT ] Source #

Binary StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

put :: StudentT -> Put Source #

get :: Get StudentT Source #

putList :: [ StudentT ] -> Put Source #

ContGen StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

genContVar :: StatefulGen g m => StudentT -> g -> m 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 #

MaybeVariance StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

maybeVariance :: StudentT -> Maybe Double Source #

maybeStdDev :: StudentT -> Maybe Double Source #

MaybeMean StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

maybeMean :: StudentT -> Maybe Double Source #

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 #

Distribution StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

Methods

cumulative :: StudentT -> Double -> Double Source #

complCumulative :: StudentT -> Double -> Double Source #

type Rep StudentT Source #
Instance details

Defined in Statistics.Distribution.StudentT

type Rep StudentT = D1 (' MetaData "StudentT" "Statistics.Distribution.StudentT" "statistics-0.16.1.2-IkOne9g3oJ1vhHVSRLPUO" ' 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 #