# statistics-linreg: Linear regression between two samples, based on the 'statistics' package.

Versions | 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.*), MonadRandom (>=0.1), random (>=1.0), random‑shuffle (>=0.0.4), safe (>=0.3), statistics (>=0.5), vector (>=0.5) [details] |

License | MIT |

Copyright | 2010-2012 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 Sat Jan 5 16:04:03 UTC 2013 |

Distributions | NixOS:0.3 |

Downloads | 3430 total (26 in the last 30 days) |

Rating | 2.0 (votes: 1) [estimated by rule of succession] |

Your Rating | |

Status | Docs uploaded by user Build status unknown [no reports yet] Hackage Matrix CI |

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.

0.2.3: 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-0.2.3.tar.gz [browse] (Cabal source package)
- Package description (as included in the package)