statistics 0.12.0.0 → 0.13.1.0

raw patch · 23 files changed

+135/−11 lines, 23 filesdep +aesonPVP ok

version bump matches the API change (PVP)

Dependencies added: aeson

API changes (from Hackage documentation)

Files

• Statistics/Distribution/Beta.hs +4/−0
• Statistics/Distribution/Binomial.hs +4/−0
• Statistics/Distribution/CauchyLorentz.hs +4/−0
• Statistics/Distribution/ChiSquared.hs +4/−0
• Statistics/Distribution/Exponential.hs +4/−0
• Statistics/Distribution/FDistribution.hs +4/−2
• Statistics/Distribution/Gamma.hs +4/−0
• Statistics/Distribution/Geometric.hs +7/−0
• Statistics/Distribution/Hypergeometric.hs +4/−0
• Statistics/Distribution/Normal.hs +4/−1
• Statistics/Distribution/Poisson.hs +4/−0
• Statistics/Distribution/StudentT.hs +4/−0
• Statistics/Distribution/Transform.hs +4/−0
• Statistics/Distribution/Uniform.hs +4/−0
• Statistics/Math/RootFinding.hs +4/−0
• Statistics/Regression.hs +38/−3
• Statistics/Resampling.hs +4/−0
• Statistics/Resampling/Bootstrap.hs +4/−0
• Statistics/Sample/KernelDensity/Simple.hs +4/−0
• Statistics/Sample/Powers.hs +4/−0
• Statistics/Test/Types.hs +12/−4
• changelog.md +4/−0
• statistics.cabal +2/−1

@@ -20,6 +20,7 @@   , bdBeta   ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -37,6 +38,9 @@  , bdBeta  :: {-# UNPACK #-} !Double    -- ^ Beta shape parameter  } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON BetaDistribution+instance ToJSON BetaDistribution  instance Binary BetaDistribution where     put (BD x y) = put x >> put y

@@ -23,6 +23,7 @@     , bdProbability     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -41,6 +42,9 @@     , bdProbability :: {-# UNPACK #-} !Double     -- ^ Probability.     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON BinomialDistribution+instance ToJSON BinomialDistribution  instance Binary BinomialDistribution where     put (BD x y) = put x >> put y

@@ -21,6 +21,7 @@   , standardCauchy   ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -40,6 +41,9 @@   , cauchyDistribScale  :: {-# UNPACK #-} !Double   }   deriving (Eq, Show, Read, Typeable, Data, Generic)++instance FromJSON CauchyDistribution+instance ToJSON CauchyDistribution  instance Binary CauchyDistribution where     put (CD x y) = put x >> put y

@@ -18,6 +18,7 @@         , chiSquaredNDF         ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -32,6 +33,9 @@ -- | Chi-squared distribution newtype ChiSquared = ChiSquared Int                      deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON ChiSquared+instance ToJSON ChiSquared  instance Binary ChiSquared where     get = fmap ChiSquared get

@@ -23,6 +23,7 @@     , edLambda     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -37,6 +38,9 @@ newtype ExponentialDistribution = ED {       edLambda :: Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON ExponentialDistribution+instance ToJSON ExponentialDistribution  instance Binary ExponentialDistribution where     put = put . edLambda

@@ -16,6 +16,7 @@   , fDistributionNDF2   ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import Numeric.MathFunctions.Constants (m_neg_inf)@@ -27,14 +28,15 @@ import Data.Binary (put, get) import Control.Applicative ((<$>), (<*>)) -- -- | F distribution data FDistribution = F { fDistributionNDF1 :: {-# UNPACK #-} !Double                        , fDistributionNDF2 :: {-# UNPACK #-} !Double                        , _pdfFactor        :: {-# UNPACK #-} !Double                        }                    deriving (Eq, Show, Read, Typeable, Data, Generic)++instance FromJSON FDistribution+instance ToJSON FDistribution  instance Binary FDistribution where     get = F <$> get <*> get <*> get

@@ -25,6 +25,7 @@     , gdScale     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Applicative ((<$>), (<*>)) import Data.Binary (Binary) import Data.Binary (put, get)@@ -41,6 +42,9 @@       gdShape :: {-# UNPACK #-} !Double -- ^ Shape parameter, /k/.     , gdScale :: {-# UNPACK #-} !Double -- ^ Scale parameter, &#977;.     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON GammaDistribution+instance ToJSON GammaDistribution  instance Binary GammaDistribution where     put (GD x y) = put x >> put y

@@ -30,6 +30,7 @@     , gdSuccess0     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Applicative ((<$>)) import Control.Monad (liftM) import Data.Binary (Binary)@@ -47,6 +48,9 @@       gdSuccess :: Double     } deriving (Eq, Read, Show, Typeable, Data, Generic) +instance FromJSON GeometricDistribution+instance ToJSON GeometricDistribution+ instance Binary GeometricDistribution where     get = GD <$> get     put (GD x) = put x@@ -113,6 +117,9 @@ newtype GeometricDistribution0 = GD0 {       gdSuccess0 :: Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON GeometricDistribution0+instance ToJSON GeometricDistribution0  instance Binary GeometricDistribution0 where     get = GD0 <$> get

@@ -27,6 +27,7 @@     , hdK     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -41,6 +42,9 @@     , hdL :: {-# UNPACK #-} !Int     , hdK :: {-# UNPACK #-} !Int     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON HypergeometricDistribution+instance ToJSON HypergeometricDistribution  instance Binary HypergeometricDistribution where     get = HD <$> get <*> get <*> get

@@ -20,6 +20,7 @@     , standard     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Applicative ((<$>), (<*>)) import Data.Binary (Binary) import Data.Binary (put, get)@@ -31,7 +32,6 @@ import qualified Statistics.Sample as S import qualified System.Random.MWC.Distributions as MWC - -- | The normal distribution. data NormalDistribution = ND {       mean       :: {-# UNPACK #-} !Double@@ -39,6 +39,9 @@     , ndPdfDenom :: {-# UNPACK #-} !Double     , ndCdfDenom :: {-# UNPACK #-} !Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON NormalDistribution+instance ToJSON NormalDistribution  instance Binary NormalDistribution where     put (ND w x y z) = put w >> put x >> put y >> put z

@@ -24,6 +24,7 @@     -- $references     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -37,6 +38,9 @@ newtype PoissonDistribution = PD {       poissonLambda :: Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON PoissonDistribution+instance ToJSON PoissonDistribution  instance Binary PoissonDistribution where     get = fmap PD get

@@ -16,6 +16,7 @@   , studentTUnstandardized   ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -28,6 +29,9 @@ -- | Student-T distribution newtype StudentT = StudentT { studentTndf :: Double }                    deriving (Eq, Show, Read, Typeable, Data, Generic)++instance FromJSON StudentT+instance ToJSON StudentT  instance Binary StudentT where     put = put . studentTndf

@@ -17,6 +17,7 @@     , scaleAround     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Applicative ((<*>)) import Data.Binary (Binary) import Data.Binary (put, get)@@ -37,6 +38,9 @@   , linTransDistr    :: d     -- ^ Distribution being transformed.   } deriving (Eq, Show, Read, Typeable, Data, Generic)++instance (FromJSON d) => FromJSON (LinearTransform d)+instance (ToJSON d) => ToJSON (LinearTransform d)  instance (Binary d) => Binary (LinearTransform d) where     get = LinearTransform <$> get <*> get <*> get

@@ -19,6 +19,7 @@     , uniformB     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Data (Data, Typeable) import GHC.Generics (Generic)@@ -33,6 +34,9 @@       uniformA :: {-# UNPACK #-} !Double -- ^ Low boundary of distribution     , uniformB :: {-# UNPACK #-} !Double -- ^ Upper boundary of distribution     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON UniformDistribution+instance ToJSON UniformDistribution  instance Binary UniformDistribution where     put (UniformDistribution x y) = put x >> put y

@@ -20,6 +20,7 @@     -- $references     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Applicative (Alternative(..), Applicative(..)) import Control.Monad (MonadPlus(..), ap) import Data.Binary (Binary)@@ -41,6 +42,9 @@             | Root a             -- ^ A root was successfully found.               deriving (Eq, Read, Show, Typeable, Data, Generic)++instance (FromJSON a) => FromJSON (Root a)+instance (ToJSON a) => ToJSON (Root a)  instance (Binary a) => Binary (Root a) where     put NotBracketed = putWord8 0

@@ -7,19 +7,54 @@  module Statistics.Regression     (-      ols+      olsRegress+    , ols     , rSquare     ) where  import Control.Applicative ((<$>))-import Prelude hiding (sum)+import Prelude hiding (pred, sum) import Statistics.Function as F-import Statistics.Matrix+import Statistics.Matrix hiding (map) import Statistics.Matrix.Algorithms (qr) import Statistics.Sample (mean) import Statistics.Sample.Internal (sum)+import qualified Data.Vector.Generic as G import qualified Data.Vector.Unboxed as U import qualified Data.Vector.Unboxed.Mutable as M++-- | Perform an ordinary least-squares regression on a set of+-- predictors, and calculate the goodness-of-fit of the regression.+--+-- The returned pair consists of:+--+-- * A vector of regression coefficients.  This vector has /one more/+--   element than the list of predictors; the last element is the+--   /y/-intercept value.+--+-- * /R&#0178;/, the coefficient of determination (see 'rSquare' for+--   details).+olsRegress :: [Vector]+              -- ^ Non-empty list of predictor vectors.  Must all have+              -- the same length.  These will become the columns of+              -- the matrix /A/ solved by 'ols'.+           -> Vector+              -- ^ Responder vector.  Must have the same length as the+              -- predictor vectors.+           -> (Vector, Double)+olsRegress preds@(_:_) resps+  | any (/=n) ls        = error $ "predictor vector length mismatch " +++                                  show lss+  | G.length resps /= n = error $ "responder/predictor length mismatch " +++                                  show (G.length resps, n)+  | otherwise           = (coeffs, rSquare mxpreds resps coeffs)+  where+    coeffs    = ols mxpreds resps+    mxpreds   = transpose .+                fromVector (length lss + 1) n .+                G.concat $ preds ++ [G.replicate n 1]+    lss@(n:ls) = map G.length preds+olsRegress _ _ = error "no predictors given"  -- | Compute the ordinary least-squares solution to /A x = b/. ols :: Matrix     -- ^ /A/ has at least as many rows as columns.

@@ -23,6 +23,7 @@     , estimate     ) where +import Data.Aeson (FromJSON, ToJSON) import Control.Concurrent (forkIO, newChan, readChan, writeChan) import Control.Monad (forM_, liftM, replicateM_) import Control.Monad.Primitive (PrimState)@@ -49,6 +50,9 @@ newtype Resample = Resample {       fromResample :: U.Vector Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON Resample+instance ToJSON Resample  instance Binary Resample where     put = put . fromResample

@@ -25,6 +25,7 @@ import Control.DeepSeq (NFData) import Control.Exception (assert) import Control.Monad.Par (parMap, runPar)+import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary) import Data.Binary (put, get) import Data.Data (Data)@@ -52,6 +53,9 @@     , estConfidenceLevel :: {-# UNPACK #-} !Double     -- ^ Confidence level of the confidence intervals.     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON Estimate+instance ToJSON Estimate  instance Binary Estimate where     put (Estimate w x y z) = put w >> put x >> put y >> put z

@@ -46,6 +46,7 @@     -- $references     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary(..)) import Data.Data (Data, Typeable) import Data.Vector.Binary ()@@ -62,6 +63,9 @@ newtype Points = Points {       fromPoints :: U.Vector Double     } deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON Points+instance ToJSON Points  instance Binary Points where     get = fmap Points get

@@ -47,6 +47,7 @@     -- $references     ) where +import Data.Aeson (FromJSON, ToJSON) import Data.Binary (Binary(..)) import Data.Data (Data, Typeable) import Data.Vector.Binary ()@@ -66,6 +67,9 @@  newtype Powers = Powers (U.Vector Double)     deriving (Eq, Read, Show, Typeable, Data, Generic)++instance FromJSON Powers+instance ToJSON Powers  instance Binary Powers where     put (Powers v) = put v

@@ -1,11 +1,13 @@-{-# LANGUAGE DeriveDataTypeable #-}+{-# LANGUAGE DeriveDataTypeable, DeriveGeneric #-} module Statistics.Test.Types (     TestType(..)   , TestResult(..)   , significant   ) where -import Data.Typeable (Typeable)+import Data.Aeson (FromJSON, ToJSON)+import Data.Data (Typeable, Data)+import GHC.Generics   -- | Test type. Exact meaning depends on a specific test. But@@ -13,12 +15,18 @@ -- for 'OneTailed' or whether it too big or too small for 'TwoTailed' data TestType = OneTailed               | TwoTailed-              deriving (Eq,Ord,Show,Typeable)+              deriving (Eq,Ord,Show,Typeable,Data,Generic) +instance FromJSON TestType+instance ToJSON TestType+ -- | Result of hypothesis testing data TestResult = Significant    -- ^ Null hypothesis should be rejected                 | NotSignificant -- ^ Data is compatible with hypothesis-                  deriving (Eq,Ord,Show,Typeable)+                  deriving (Eq,Ord,Show,Typeable,Data,Generic)++instance FromJSON TestResult+instance ToJSON TestResult  -- | Significant if parameter is 'True', not significant otherwiser significant :: Bool -> TestResult

@@ -1,3 +1,7 @@+Changes in 0.13.0.0++  * All types now support JSON encoding and decoding.+ Changes in 0.12.0.0    * The `Statistics.Math` module has been removed, after being

@@ -1,5 +1,5 @@ name:           statistics-version:        0.12.0.0+version:        0.13.1.0 synopsis:       A library of statistical types, data, and functions description:   This library provides a number of common functions and types useful@@ -95,6 +95,7 @@     Statistics.Sample.Internal     Statistics.Test.Internal   build-depends:+    aeson >= 0.6.0.0,     base >= 4.4 && < 5,     binary >= 0.5.1.0,     deepseq >= 1.1.0.2,