statistics-0.13.3.0: 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

Description

Student-T distribution

Synopsis

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

# Documentation

data StudentT Source #

Student-T distribution

Instances

Eq StudentT Source # |
Methods (==) :: StudentT -> StudentT -> Bool # (/=) :: StudentT -> StudentT -> Bool #
Data StudentT Source # |

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 :: (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 #

Read StudentT Source # |
Methods readsPrec :: Int -> ReadS StudentT # readList :: ReadS [StudentT] # readPrec :: ReadPrec StudentT # readListPrec :: ReadPrec [StudentT] #
Show StudentT Source # |
Methods showsPrec :: Int -> StudentT -> ShowS # show :: StudentT -> String # showList :: [StudentT] -> ShowS #
Generic StudentT Source # |
Associated Types type Rep StudentT :: * -> * # Methods from :: StudentT -> Rep StudentT x # to :: Rep StudentT x -> StudentT #
ToJSON StudentT Source # |
Methods toJSON :: StudentT -> Value # toEncoding :: StudentT -> Encoding # toJSONList :: [StudentT] -> Value # toEncodingList :: [StudentT] -> Encoding #
FromJSON StudentT Source # |
Methods parseJSON :: Value -> Parser StudentT # parseJSONList :: Value -> Parser [StudentT] #
Binary StudentT Source # |
Methods put :: StudentT -> Put # get :: Get StudentT # putList :: [StudentT] -> Put #
ContGen StudentT Source # |
Methods genContVar :: PrimMonad m => StudentT -> Gen (PrimState m) -> m Double Source #
Entropy StudentT Source # |
Methods entropy :: StudentT -> Double Source #
MaybeEntropy StudentT Source # |
Methods maybeEntropy :: StudentT -> Maybe Double Source #
MaybeVariance StudentT Source # |
Methods maybeVariance :: StudentT -> Maybe Double Source # maybeStdDev :: StudentT -> Maybe Double Source #
MaybeMean StudentT Source # |
Methods maybeMean :: StudentT -> Maybe Double Source #
ContDistr StudentT Source # |
Methods density :: StudentT -> Double -> Double Source # quantile :: StudentT -> Double -> Double Source # logDensity :: StudentT -> Double -> Double Source #
Distribution StudentT Source # |
Methods cumulative :: StudentT -> Double -> Double Source # complCumulative :: StudentT -> Double -> Double Source #
type Rep StudentT Source # |
type Rep StudentT = D1 (MetaData "StudentT" "Statistics.Distribution.StudentT" "statistics-0.13.3.0-Fvkducafmyw9ljEnBhS6Nm" True) (C1 (MetaCons "StudentT" PrefixI True) (S1 (MetaSel (Just Symbol "studentTndf") NoSourceUnpackedness NoSourceStrictness DecidedLazy) (Rec0 Double)))

studentT :: Double -> StudentT Source #

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

studentTndf :: StudentT -> Double Source #

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.