Provides functions to perform a linear regression between 2 samples, see the documentation of the linearRegression functions. This library is based on the
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.
import qualified Data.Vector.Unboxed as U test :: Int -> IO () test k = do let n = 10000000 let a = k*n + 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.