statistics-0.16.1.2: A library of statistical types, data, and functions
Copyright (c) 2013 John McDonnell;
License BSD3
Maintainer bos@serpentine.com
Stability experimental
Portability portable
Safe Haskell None
Language Haskell2010

Statistics.Distribution.Transform

Description

Transformations over distributions

Synopsis

Documentation

data LinearTransform d Source #

Linear transformation applied to distribution. 

LinearTransform μ σ _
x' = μ + σ·x

Constructors

LinearTransform

Fields

Instances

Instances details
Functor LinearTransform Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

fmap :: (a -> b) -> LinearTransform a -> LinearTransform b Source #

(<$) :: a -> LinearTransform b -> LinearTransform a Source #

Eq d => Eq ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

(==) :: LinearTransform d -> LinearTransform d -> Bool Source #

(/=) :: LinearTransform d -> LinearTransform d -> Bool Source #

Data d => Data ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

gfoldl :: ( forall d0 b. Data d0 => c (d0 -> b) -> d0 -> c b) -> ( forall g. g -> c g) -> LinearTransform d -> c ( LinearTransform d) Source #

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

toConstr :: LinearTransform d -> Constr Source #

dataTypeOf :: LinearTransform d -> DataType Source #

dataCast1 :: Typeable t => ( forall d0. Data d0 => c (t d0)) -> Maybe (c ( LinearTransform d)) Source #

dataCast2 :: Typeable t => ( forall d0 e. ( Data d0, Data e) => c (t d0 e)) -> Maybe (c ( LinearTransform d)) Source #

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

gmapQl :: (r -> r' -> r) -> r -> ( forall d0. Data d0 => d0 -> r') -> LinearTransform d -> r Source #

gmapQr :: forall r r'. (r' -> r -> r) -> r -> ( forall d0. Data d0 => d0 -> r') -> LinearTransform d -> r Source #

gmapQ :: ( forall d0. Data d0 => d0 -> u) -> LinearTransform d -> [u] Source #

gmapQi :: Int -> ( forall d0. Data d0 => d0 -> u) -> LinearTransform d -> u Source #

gmapM :: Monad m => ( forall d0. Data d0 => d0 -> m d0) -> LinearTransform d -> m ( LinearTransform d) Source #

gmapMp :: MonadPlus m => ( forall d0. Data d0 => d0 -> m d0) -> LinearTransform d -> m ( LinearTransform d) Source #

gmapMo :: MonadPlus m => ( forall d0. Data d0 => d0 -> m d0) -> LinearTransform d -> m ( LinearTransform d) Source #

Read d => Read ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

readsPrec :: Int -> ReadS ( LinearTransform d) Source #

readList :: ReadS [ LinearTransform d] Source #

readPrec :: ReadPrec ( LinearTransform d) Source #

readListPrec :: ReadPrec [ LinearTransform d] Source #

Show d => Show ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

showsPrec :: Int -> LinearTransform d -> ShowS Source #

show :: LinearTransform d -> String Source #

showList :: [ LinearTransform d] -> ShowS Source #

Generic ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Associated Types

type Rep ( LinearTransform d) :: Type -> Type Source #

Methods

from :: LinearTransform d -> Rep ( LinearTransform d) x Source #

to :: Rep ( LinearTransform d) x -> LinearTransform d Source #

ToJSON d => ToJSON ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

toJSON :: LinearTransform d -> Value Source #

toEncoding :: LinearTransform d -> Encoding Source #

toJSONList :: [ LinearTransform d] -> Value Source #

toEncodingList :: [ LinearTransform d] -> Encoding Source #

FromJSON d => FromJSON ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

parseJSON :: Value -> Parser ( LinearTransform d) Source #

parseJSONList :: Value -> Parser [ LinearTransform d] Source #

Binary d => Binary ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

put :: LinearTransform d -> Put Source #

get :: Get ( LinearTransform d) Source #

putList :: [ LinearTransform d] -> Put Source #

ContGen d => ContGen ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

genContVar :: StatefulGen g m => LinearTransform d -> g -> m Double Source #

Entropy d => Entropy ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

entropy :: LinearTransform d -> Double Source #

MaybeEntropy d => MaybeEntropy ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

maybeEntropy :: LinearTransform d -> Maybe Double Source #

Variance d => Variance ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

variance :: LinearTransform d -> Double Source #

stdDev :: LinearTransform d -> Double Source #

MaybeVariance d => MaybeVariance ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

maybeVariance :: LinearTransform d -> Maybe Double Source #

maybeStdDev :: LinearTransform d -> Maybe Double Source #

Mean d => Mean ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

mean :: LinearTransform d -> Double Source #

MaybeMean d => MaybeMean ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

maybeMean :: LinearTransform d -> Maybe Double Source #

ContDistr d => ContDistr ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

density :: LinearTransform d -> Double -> Double Source #

logDensity :: LinearTransform d -> Double -> Double Source #

quantile :: LinearTransform d -> Double -> Double Source #

complQuantile :: LinearTransform d -> Double -> Double Source #

Distribution d => Distribution ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

Methods

cumulative :: LinearTransform d -> Double -> Double Source #

complCumulative :: LinearTransform d -> Double -> Double Source #

type Rep ( LinearTransform d) Source #
Instance details

Defined in Statistics.Distribution.Transform

type Rep ( LinearTransform d) = D1 (' MetaData "LinearTransform" "Statistics.Distribution.Transform" "statistics-0.16.1.2-IkOne9g3oJ1vhHVSRLPUO" ' False ) ( C1 (' MetaCons "LinearTransform" ' PrefixI ' True ) ( S1 (' MetaSel (' Just "linTransLocation") ' SourceUnpack ' SourceStrict ' DecidedStrict ) ( Rec0 Double ) :*: ( S1 (' MetaSel (' Just "linTransScale") ' SourceUnpack ' SourceStrict ' DecidedStrict ) ( Rec0 Double ) :*: S1 (' MetaSel (' Just "linTransDistr") ' NoSourceUnpackedness ' NoSourceStrictness ' DecidedLazy ) ( Rec0 d))))

linTransFixedPoint :: LinearTransform d -> Double Source #

Get fixed point of linear transformation

scaleAround Source #

Arguments

:: Double

Fixed point

-> Double

Scale parameter

-> d

Distribution

-> LinearTransform d

Apply linear transformation to distribution.