statistics-0.16.2.1: A library of statistical types, data, and functions
Copyright(c) 2011 Aleksey Khudyakov
LicenseBSD3
Maintainerbos@serpentine.com
Stabilityexperimental
Portabilityportable
Safe HaskellSafe-Inferred
LanguageHaskell2010

Statistics.Distribution.StudentT

Description

Student-T distribution

Synopsis

Documentation

data StudentT Source #

Student-T distribution

Instances

Instances details
FromJSON StudentT Source # 
Instance details

Defined in Statistics.Distribution.StudentT

ToJSON StudentT Source # 
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Defined in Statistics.Distribution.StudentT

Data StudentT Source # 
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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 # 
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Defined in Statistics.Distribution.StudentT

Show StudentT Source # 
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Binary StudentT Source # 
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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

ContDistr StudentT Source # 
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Defined in Statistics.Distribution.StudentT

ContGen StudentT Source # 
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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

Entropy StudentT Source # 
Instance details

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MaybeEntropy StudentT Source # 
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Defined in Statistics.Distribution.StudentT

MaybeMean StudentT Source # 
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MaybeVariance StudentT Source # 
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Defined in Statistics.Distribution.StudentT

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