statistics-0.16.2.1: A library of statistical types, data, and functions

Copyright | (c) 2010 Alexey Khudyakov
License | BSD3
Maintainer | bos@serpentine.com
Stability | experimental
Portability | portable
Safe Haskell | Safe-Inferred
Language | Haskell2010

Statistics.Distribution.ChiSquared

Contents

- Constructors

Description

The chi-squared distribution. This is a continuous probability distribution of sum of squares of k independent standard normal distributions. It's commonly used in statistical tests

Synopsis

- data ChiSquared
- chiSquaredNDF :: ChiSquared -> Int
- chiSquared :: Int -> ChiSquared
- chiSquaredE :: Int -> Maybe ChiSquared

# Documentation

data ChiSquared Source #

Chi-squared distribution

#### Instances

Instances details

FromJSON ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods parseJSON :: Value -> Parser ChiSquared Source # parseJSONList :: Value -> Parser [ChiSquared] Source #
ToJSON ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods toJSON :: ChiSquared -> Value Source # toEncoding :: ChiSquared -> Encoding Source # toJSONList :: [ChiSquared] -> Value Source # toEncodingList :: [ChiSquared] -> Encoding Source #
Data ChiSquared Source # |

Instance details

Defined in Statistics.Distribution.ChiSquared

Methods

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

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

toConstr :: ChiSquared -> Constr Source #

dataTypeOf :: ChiSquared -> DataType Source #

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

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

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

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

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

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

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

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

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

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

Generic ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Associated Types type Rep ChiSquared :: Type -> Type Source # Methods from :: ChiSquared -> Rep ChiSquared x Source # to :: Rep ChiSquared x -> ChiSquared Source #
Read ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods readsPrec :: Int -> ReadS ChiSquared Source # readList :: ReadS [ChiSquared] Source # readPrec :: ReadPrec ChiSquared Source # readListPrec :: ReadPrec [ChiSquared] Source #
Show ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods showsPrec :: Int -> ChiSquared -> ShowS Source # show :: ChiSquared -> String Source # showList :: [ChiSquared] -> ShowS Source #
Binary ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods put :: ChiSquared -> Put Source # get :: Get ChiSquared Source # putList :: [ChiSquared] -> Put Source #
Eq ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods (==) :: ChiSquared -> ChiSquared -> Bool Source # (/=) :: ChiSquared -> ChiSquared -> Bool Source #
ContDistr ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods density :: ChiSquared -> Double -> Double Source # logDensity :: ChiSquared -> Double -> Double Source # quantile :: ChiSquared -> Double -> Double Source # complQuantile :: ChiSquared -> Double -> Double Source #
ContGen ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods genContVar :: StatefulGen g m => ChiSquared -> g -> m Double Source #
Distribution ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods cumulative :: ChiSquared -> Double -> Double Source # complCumulative :: ChiSquared -> Double -> Double Source #
Entropy ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods entropy :: ChiSquared -> Double Source #
MaybeEntropy ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeEntropy :: ChiSquared -> Maybe Double Source #
MaybeMean ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeMean :: ChiSquared -> Maybe Double Source #
MaybeVariance ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods maybeVariance :: ChiSquared -> Maybe Double Source # maybeStdDev :: ChiSquared -> Maybe Double Source #
Mean ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods mean :: ChiSquared -> Double Source #
Variance ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared Methods variance :: ChiSquared -> Double Source # stdDev :: ChiSquared -> Double Source #
type Rep ChiSquared Source # |
Instance details Defined in Statistics.Distribution.ChiSquared type Rep ChiSquared = D1 ('MetaData "ChiSquared" "Statistics.Distribution.ChiSquared" "statistics-0.16.2.1-An1XEEv5tKOFj5G6JDoeTv" 'True) (C1 ('MetaCons "ChiSquared" 'PrefixI 'True) (S1 ('MetaSel ('Just "chiSquaredNDF") 'NoSourceUnpackedness 'NoSourceStrictness 'DecidedLazy) (Rec0 Int)))

chiSquaredNDF :: ChiSquared -> Int Source #

Get number of degrees of freedom

# Constructors

chiSquared :: Int -> ChiSquared Source #

Construct chi-squared distribution. Number of degrees of freedom must be positive.

chiSquaredE :: Int -> Maybe ChiSquared Source #

Construct chi-squared distribution. Number of degrees of freedom must be positive.