statistics is:package

A library of statistical types, data, and functions This library provides a number of common functions and types useful in statistics. We focus on high performance, numerical robustness, and use of good algorithms. Where possible, we provide references to the statistical literature. . The library's facilities can be divided into four broad categories: . * Working with widely used discrete and continuous probability distributions. (There are dozens of exotic distributions in use; we focus on the most common.) . * Computing with sample data: quantile estimation, kernel density estimation, histograms, bootstrap methods, significance testing, and regression and autocorrelation analysis. . * Random variate generation under several different distributions. . * Common statistical tests for significant differences between samples.

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.

Not on Stackage, so not searched. Functions for working with Dirichlet densities and mixtures on vectors.

Not on Stackage, so not searched. An implementation of high performance, minimal statistics functions

Not on Stackage, so not searched. Random variate generation from hypergeometric distributions

Not on Stackage, so not searched. A library of statistical types, data, and functions

Not on Stackage, so not searched. Statistical functions from the statistics package implemented as Folds.

Not on Stackage, so not searched. Monoids for calculation of statistics of sample

Statistics Purely functional interface for statistics based on hmatrix and hmatrix-gsl-stats The vector type is Data.Vector.Storable from the vector package and compatible with the statistics package. http://hackage.haskell.org/package/statistics Feature requests, suggestions, and bug fixes welcome.

Not on Stackage, so not searched. L-Estimators for robust statistics

Not on Stackage, so not searched. Statistical measures for finite or infinite data streams.

Not on Stackage, so not searched. Interactive domain reasoner for statistics