statistics-0.15.0.0: 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 | Haskell98

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

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 :: (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 :: PrimMonad m => StudentT -> Gen (PrimState m) -> 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 # quantile :: StudentT -> Double -> Double Source # complQuantile :: StudentT -> Double -> Double Source # logDensity :: 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-0.15.0.0-6JZeW98TNbBJdNHw3GDX0L" 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 #