ghc-statistics-linreg

Provides functions to perform a linear regression between 2 samples, see the
documentation of the linearRegression functions. This library is based on the
'statistics' package.

0.3: you can now use all functions on any instance of the Vector class (not

just unboxed vectors).

0.2.4: added distribution estimations for standard regression parameters.

0.2.3: added robust-fit support.

0.2.2: added the Total-Least-Squares version and made some refactoring to


eliminate code duplication

0.2.1: added the r-squared version and improved the performances.

Code sample:
> import qualified Data.Vector.Unboxed as U > > test :: Int -> IO () > test k =
do > let n = 10000000 > let a = kn + 1 > let b = (k+1)n > let xs = U.fromList
[a..b] > let ys = U.map (x -> x*100 + 2000) xs > -- thus 100 and 2000 are the
alpha and beta we want > putStrLn "linearRegression:" > print $
linearRegression xs ys
The r-squared and Total-Least-Squares versions work the same way.

          

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License: MIT
URL: https://hackage.haskell.org/package/statistics-linreg