statistics 0.8.0.2 → 0.8.0.3
raw patch · 6 files changed
+55/−253 lines, 6 files
Files
- README +0/−47
- README.markdown +52/−0
- Statistics/Distribution/Beta.hs +0/−51
- Statistics/Distribution/LogNormal.hs +0/−81
- Statistics/Distribution/Triangular.hs +0/−68
- statistics.cabal +3/−6
− README
@@ -1,47 +0,0 @@-Statistics: efficient, general purpose statistics----------------------------------------------------This package provides the Statistics module, a Haskell library for-working with statistical data in a space- and time-efficient way.--Where possible, we give citations and computational complexity-estimates for the algorithms used.---Performance--------------This library has been carefully optimised for high performance. To-obtain the best runtime efficiency, it is imperative to compile-libraries and applications that use this library using a high level of-optimisation.--Suggested GHC options:-- -O -fvia-C -funbox-strict-fields--To illustrate, here are the times (in seconds) to generate and sum 250-million random Word32 values, on a laptop with a 2.4GHz Core2 Duo-P8600 processor, running Fedora 11 and GHC 6.10.3:-- no flags 200+- -O 1.249- -O -fvia-C 0.991--As the numbers above suggest, compiling without optimisation will-yield unacceptable performance.---Get involved!----------------Please feel welcome to contribute new code or bug fixes. You can-fetch the source repository from here:--http://bitbucket.org/bos/statistics---Authors----------Bryan O'Sullivan <bos@serpentine.com>
+ README.markdown view
@@ -0,0 +1,52 @@+# Statistics: efficient, general purpose statistics++This package provides the Statistics module, a Haskell library for+working with statistical data in a space- and time-efficient way.++Where possible, we give citations and computational complexity+estimates for the algorithms used.+++# Performance++This library has been carefully optimised for high performance. To+obtain the best runtime efficiency, it is imperative to compile+libraries and applications that use this library using a high level of+optimisation.++Suggested GHC options:++ -O -funbox-strict-fields++To illustrate, here are the times (in seconds) to generate and sum 250+million random Word32 values, on a laptop with a 2.4GHz Core2 Duo+P8600 processor, running Fedora 11 and GHC 6.10.3:++ no flags 200++ -O 1.249+ -O -fvia-C 0.991++As the numbers above suggest, compiling without optimisation will+yield unacceptable performance.+++# Get involved!++Please report bugs via the+[bitbucket issue tracker](http://bitbucket.org/bos/attoparsec/statistics).++Master [Mercurial repository](http://bitbucket.org/bos/statistics):++* `hg clone http://bitbucket.org/bos/statistics`++There's also a [git mirror](http://github.com/bos/statistics):++* `git clone git://github.com/bos/statistics.git`++(You can create and contribute changes using either Mercurial or git.)+++# Authors++This library is written and maintained by Bryan O'Sullivan,+<bos@serpentine.com>.
− Statistics/Distribution/Beta.hs
@@ -1,51 +0,0 @@-{-# LANGUAGE DeriveDataTypeable #-}--- |--- Module : Statistics.Distribution.Beta--- Copyright : (c) 2010 Karamaan Group------ The beta distribution.--module Statistics.Distribution.Beta- (- BetaDistribution- -- * Constructors- , fromParams- -- * Accessors- , tridistA- , tridistB- , tridistC- ) where--import Control.Exception-import Data.Generics-import Foreign.C.Math.Double (gamma)-import qualified Statistics.Distribution as D--data BetaDistribution = BetaDist {- alpha :: Double,- beta :: Double-} deriving (Eq, Read, Show, Typeable, Data)--instance D.Distribution BetaDistribution where- density (BetaDist a b) x = (gamma (a+b) / (gamma a * gamma b)) *- (x**(a-1)) * ((1-x)**(b-1))- {-# INLINE density #-}- cumulative (BetaDist a b) x = undefined- {-# INLINE cumulative #-}- quantile (BetaDist a b) p = undefined- {-# INLINE quantile #-}--instance D.Variance BetaDistribution where- variance (BetaDist a b) = (a * b) /- ((a+b)^2 * (a + b + 1))- {-# INLINE variance #-}--instance D.Mean BetaDistribution where- mean (BetaDist a b) = a / (a + b)- {-# INLINE mean #-}--fromParams :: Double -> Double -> BetaDistribution-fromParams a b = assert (a > 0 && b > 0) (BetaDist a b)-{-# INLINE fromParams #-}--
− Statistics/Distribution/LogNormal.hs
@@ -1,81 +0,0 @@-{-# LANGUAGE DeriveDataTypeable #-}--- |--- Module : Statistics.Distribution.LogNormal--- Copyright : (c) 2009 Karamaan Group------ The lognormal distribution. This is the distribution of a random --- variable whose logarithm is normally distributed.--module Statistics.Distribution.LogNormal- (- LogNormalDistribution- -- * Constructors- , fromParams- , standard- ) where--import Control.Exception (assert)-import Data.Number.Erf (erf)-import Data.Generics-import Statistics.Constants (m_sqrt_2, m_sqrt_2_pi)-import qualified Statistics.Distribution as D---- | The lognormal distribution.-data LogNormalDistribution = ND {- mean :: {-# UNPACK #-} !Double- , variance :: {-# UNPACK #-} !Double- , ndPdfDenom :: {-# UNPACK #-} !Double- , ndCdfDenom :: {-# UNPACK #-} !Double- } deriving (Eq, Read, Show, Typeable, Data)--instance D.Distribution LogNormalDistribution where- density = density- cumulative = cumulative- quantile = quantile--instance D.Variance LogNormalDistribution where- variance = variance--instance D.Mean LogNormalDistribution where- mean = mean--standard :: LogNormalDistribution-standard = ND {- mean = 0.0- , variance = 1.0- , ndPdfDenom = m_sqrt_2_pi- , ndCdfDenom = m_sqrt_2- }--fromParams :: Double -> Double -> LogNormalDistribution-fromParams m v = assert (v > 0)- ND {- mean = m- , variance = v- , ndPdfDenom = m_sqrt_2_pi * sv- , ndCdfDenom = m_sqrt_2 * sv- }- where sv = sqrt v--density :: LogNormalDistribution -> Double -> Double-density d x = exp (-xm * xm / (2 * variance d)) / (x * ndPdfDenom d)- where xm = log x - mean d--cumulative :: LogNormalDistribution -> Double -> Double-cumulative d x = (1 + erf ((log x-mean d) / ndCdfDenom d)) / 2---- | This is the quantile function for the LogNormalDistribution.-quantile :: LogNormalDistribution -> Double -> Double-quantile d p = exp $ quantile' d p---- | This is the quantile function for NormalDistribution.-quantile' :: LogNormalDistribution -> Double -> Double-quantile' d p- | p < 0 || p > 1 = inf/inf- | p == 0 = -inf- | p == 1 = inf- | p == 0.5 = mean d- | otherwise = x * sqrt (variance d) + mean d- where x = D.findRoot standard p 0 (-100) 100- inf = 1/0-
− Statistics/Distribution/Triangular.hs
@@ -1,68 +0,0 @@-{-# LANGUAGE DeriveDataTypeable #-}--- |--- Module : Statistics.Distribution.Triangular--- Copyright : (c) 2010 Karamaan Group------ The triangular distribution. This is the distribution of a random --- variable with lower limit a, mode c and upper limit b.--module Statistics.Distribution.Triangular- (- TriangularDistribution- -- * Constructors- , fromParams- -- * Accessors- , tridistA- , tridistB- , tridistC- ) where--import Data.Generics-import qualified Statistics.Distribution as D--data TriangularDistribution = TriDist {- tridistA :: Double, -- min- tridistB :: Double, -- max- tridistC :: Double -- mode-} deriving (Eq, Read, Show, Typeable, Data)--instance D.Distribution TriangularDistribution where- density (TriDist a b c) x- | (a <= x) && (x <= c) = (2 * (x - a)) / ((b - a) * (c - a))- | (c <= x) && (x <= b) = (2 * (b - x)) / ((b - a) * (b - c))- | otherwise = 0- {-# INLINE density #-}-- cumulative (TriDist a b c) x- | a > x = 0- | (a <= x) && (x <= c) = ((x - a) ^ 2) / ((b - a) * (c - a))- | (c <= x) && (x <= b) = 1 - ((b - x) ^ 2) / ((b - a) * (b - c))- | otherwise = 1- {-# INLINE cumulative #-}-- quantile (TriDist a b c) p = calc ((c - a) / (b - a))- where calc p0- | p < p0 = sqrt ((b-a) * (c-a) * p) + a- | p == p0 = c- | otherwise = b - sqrt ((b-a) * (b-c) * (1-p))- {-# INLINE quantile #-}--instance D.Variance TriangularDistribution where- variance (TriDist a b c) =- (a^2 + b^2 + c^2 - (a*b) - (a*c) - (b*c)) / 18- {-# INLINE variance #-}--instance D.Mean TriangularDistribution where- mean (TriDist a b c) = (a + b + c) / 3- {-# INLINE mean #-}--fromParams :: Double -> Double -> Double -> TriangularDistribution-fromParams a b c - | (c > b) || (c < a) = error $ "Triangular Distribution: Parameter " ++ (show c)- ++ " is expected to be between the parameters " - ++ (show a) ++ " and " ++ (show b) ++ "."- | b < a = error $ "Triangular Distribution: Parameter " ++ (show b)- ++ " is expected to be greater than parameter " ++ (show a) ++ "."- | otherwise = TriDist a b c-{-# INLINE fromParams #-}-
statistics.cabal view
@@ -1,5 +1,5 @@ name: statistics-version: 0.8.0.2+version: 0.8.0.3 synopsis: A library of statistical types, data, and functions description: This library provides a number of common functions and types useful@@ -30,24 +30,21 @@ category: Math, Statistics build-type: Simple cabal-version: >= 1.6-extra-source-files: README+extra-source-files: README.markdown library exposed-modules: Statistics.Autocorrelation Statistics.Constants Statistics.Distribution- Statistics.Distribution.Beta Statistics.Distribution.Binomial Statistics.Distribution.ChiSquared- Statistics.Distribution.Exponential Statistics.Distribution.Gamma Statistics.Distribution.Geometric+ Statistics.Distribution.Exponential Statistics.Distribution.Hypergeometric- Statistics.Distribution.LogNormal Statistics.Distribution.Normal Statistics.Distribution.Poisson- Statistics.Distribution.Triangular Statistics.Function Statistics.KernelDensity Statistics.Math