I'm pleased to announce a major release of of the Haskell statistics library, version 0.10.0.0.
I'd particularly like to thank Alexey Khudyakov for his wonderful work on this release.
Student-T, Fisher-Snedecor, F-distribution, and Cauchy-Lorentz distributions are added.
Histogram computation is added, in
Forward and inverse discrete Fourier and cosine transforms are added, in
Root finding is added, in
Sample.KernelDensitymodule has been renamed, and completely rewritten to be much more robust. The older module oversmoothed multi-modal data. (The older module is still available under the name
The type classes
Varianceare split in two. This is required for distributions which do not have finite variance or mean.
complCumulativefunction is added to the
Distributionclass in order to accurately assess probalities P(X>x) which are used in one-tailed tests.
stdDevfunction is added to the
Varianceclass for distributions.
Distribution.normalDistrnow takes standard deviation instead of variance as its parameter.
A bug in
Quantile.weightedAvgis fixed. It produced a wrong answer if a sample contained only one element.
Bugs in quantile estimations for chi-square and gamma distribution are fixed.
Integer overlow in
mannWhitneyUCriticalValueis fixed. It produced incorrect critical values for moderately large samples. Something around 20 for 32-bit machines and 40 for 64-bit ones.
A bug in
mannWhitneyUSignificantis fixed. If either sample was larger than 20, it produced a completely incorrect answer.
One- and two-tailed tests in
Tests.NonParametricare selected with sum types instead of
Test results returned as enumeration instead of
Performance improvements for Mann-Whitney U and Wilcoxon tests.
Tests.NonParamtricis split into
sortByis added to
Mean and variance for gamma distribution are fixed.
Much faster cumulative probablity functions for Poisson and hypergeometric distributions.
Better density functions for gamma and Poisson distributions.
Function.createis removed. Use
A function to perform approximate comparion of doubles is added to
Regularized incomplete beta function and its inverse are added to