statistics 0.2 → 0.2.1

raw patch · 6 files changed

+29/−26 lines, 6 files

Files

• Statistics/Constants.hs +1/−1
• Statistics/Function.hs +15/−1
• Statistics/Resampling.hs +1/−12
• Statistics/Sample.hs +9/−9
• Statistics/Types.hs +2/−2
• statistics.cabal +1/−1

@@ -22,7 +22,7 @@  -- | A very large number. m_huge :: Double-m_huge = 1.797693e308+m_huge = 1.7976931348623157e308 {-# INLINE m_huge #-}  -- | The largest 'Int' /x/ such that 2**(/x/-1) is approximately

@@ -15,10 +15,13 @@       minMax     , sort     , partialSort+    , createU     ) where +import Control.Exception (assert)+import Control.Monad.ST (unsafeSTToIO) import Data.Array.Vector.Algorithms.Combinators (apply)-import Data.Array.Vector ((:*:)(..), UA, UArr, foldlU)+import Data.Array.Vector import qualified Data.Array.Vector.Algorithms.Intro as I  -- | Sort an array.@@ -44,3 +47,14 @@     go (MM lo hi) k = MM (min lo k) (max hi k)     fini (MM lo hi) = lo :*: hi {-# INLINE minMax #-}++-- | Create an array, using the given action to populate each element.+createU :: (UA e) => Int -> (Int -> IO e) -> IO (UArr e)+createU size itemAt = assert (size >= 0) $+    unsafeSTToIO (newMU size) >>= loop 0+  where+    loop k arr | k >= size = unsafeSTToIO (unsafeFreezeAllMU arr)+               | otherwise = do+      r <- itemAt k+      unsafeSTToIO (writeMU arr k r)+      loop (k+1) arr

@@ -16,11 +16,11 @@     , resample     ) where -import Control.Exception (assert) import Control.Monad (forM_) import Control.Monad.ST (unsafeSTToIO) import Data.Array.Vector import Data.Array.Vector.Algorithms.Intro (sort)+import Statistics.Function (createU) import Statistics.Types (Estimator, Sample) import System.Random.Mersenne (MTGen, random) @@ -50,17 +50,6 @@         writeMU arr k . est $ re     loop (k+1) ers   n = lengthU samples---- | Create an array, using the given action to populate each element.-createU :: (UA e) => Int -> (Int -> IO e) -> IO (UArr e)-createU size itemAt = assert (size >= 0) $-    unsafeSTToIO (newMU size) >>= loop 0-  where-    loop k arr | k >= size = unsafeSTToIO (unsafeFreezeAllMU arr)-               | otherwise = do-      r <- itemAt k-      unsafeSTToIO (writeMU arr k r)-      loop (k+1) arr  -- | Compute a statistical estimate repeatedly over a sample, each -- time omitting a successive element.

@@ -38,7 +38,7 @@     -- $references     ) where -import Data.Array.Vector (foldlU)+import Data.Array.Vector (foldlU, lengthU) import Statistics.Types (Sample)  -- | Arithmetic mean.  This uses Welford's algorithm to provide@@ -83,16 +83,16 @@ -- Because of the need for two passes, these functions are /not/ -- subject to stream fusion. +data V = V {-# UNPACK #-} !Double {-# UNPACK #-} !Double+ robustVar :: Sample -> T-robustVar samp = fini . foldlU go (T1 0 0 0) $ samp+robustVar samp = fini . foldlU go (V 0 0) $ samp   where-    go (T1 n s c) x = T1 n' s' c'-      where n' = n + 1-            s' = s + d * d-            c' = c + d-            d  = x - m-    fini (T1 n s c) = T (s - c ** (2 / fromIntegral n)) n-    m = mean samp+    go (V s c) x = V (s + d * d) (c + d)+        where d  = x - m+    fini (V s c) = T (s - (c * c) / fromIntegral n) n+    n            = lengthU samp+    m            = mean samp  -- | Maximum likelihood estimate of a sample's variance. variance :: Sample -> Double

@@ -11,8 +11,8 @@  module Statistics.Types     (-      Sample-    , Estimator+      Estimator+    , Sample     , Weights     ) where 

@@ -1,5 +1,5 @@ name:           statistics-version:        0.2+version:        0.2.1 synopsis:       A library of statistical types, data, and functions description:   This library provides a number of common functions and types useful