statistics-linreg: Linear regression between two samples, based on the 'statistics' package.
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 = 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.
Downloads
- statistics-linreg-0.3.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)
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Versions [RSS] | 0.1, 0.2, 0.2.1, 0.2.2, 0.2.3, 0.2.4, 0.3 |
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Dependencies | base (>=4 && <5), MonadRandom (>=0.1), random (>=1.0), random-shuffle (>=0.0.4), safe (>=0.3), statistics (>=0.5), vector (>=0.5) [details] |
License | MIT |
Copyright | 2010-2014 Alp Mestanogullari |
Author | Alp Mestanogullari <alpmestan@gmail.com>, Uri Barenholz <uri.barenholz@weizmann.ac.il> |
Maintainer | Alp Mestanogullari <alpmestan@gmail.com> |
Category | Math, Statistics |
Home page | http://github.com/alpmestan/statistics-linreg |
Bug tracker | https://github.com/alpmestan/statistics-linreg/issues |
Source repo | head: git clone http://github.com/alpmestan/statistics-linreg.git |
Uploaded | by AlpMestanogullari at 2014-08-22T08:41:25Z |
Distributions | LTSHaskell:0.3, NixOS:0.3, Stackage:0.3 |
Reverse Dependencies | 2 direct, 1 indirect [details] |
Downloads | 20237 total (153 in the last 30 days) |
Rating | 2.0 (votes: 1) [estimated by Bayesian average] |
Your Rating | |
Status | Docs available [build log] Successful builds reported [all 1 reports] |