Changelog of @hackage/statistics 0.11.0.3

-- text --

Changes in 0.10.6.0

  • The Estimator type has become an algebraic data type. This allows the jackknife function to potentially use more efficient jackknife implementations.

  • jackknifeMean, jackknifeStdDev, jackknifeVariance, jackknifeVarianceUnb: new functions. These have O(n) cost instead of the O(n^2) cost of the standard jackknife.

  • The mean function has been renamed to welfordMean; a new implementation of mean has better numerical accuracy in almost all cases.

Changes in 0.10.5.2

  • histogram correctly chooses range when all elements in the sample are same (bug #57)

Changes in 0.10.5.1

  • Bug fix for S.Distributions.Normal.standard introduced in 0.10.5.0 (Bug #56)

Changes in 0.10.5.0

  • Enthropy type class for distributions is added.

  • Probability and probability density of distribution is given in log domain too.

Changes in 0.10.4.0

  • Support for versions of GHC older than 7.2 is discontinued.

  • All datatypes now support 'Data.Binary' and 'GHC.Generics'.

Changes in 0.10.3.0

  • Bug fixes

Changes in 0.10.2.0

  • Bugs in DCT and IDCT are fixed.

  • Accesors for uniform distribution are added.

  • ContGen instances for all continous distribtuions are added.

  • Beta distribution is added.

  • Constructor for improper gamma distribtuion is added.

  • Binomial distribution allows zero trials.

  • Poisson distribution now accept zero parameter.

  • Integer overflow in caculation of Wilcoxon-T test is fixed.

  • Bug in 'ContGen' instance for normal distribution is fixed.

Changes in 0.10.1.0

  • Kolmogorov-Smirnov nonparametric test added.

  • Pearson chi squared test added.

  • Type class for generating random variates for given distribution is added.

  • Modules 'Statistics.Math' and 'Statistics.Constants' are moved to the @math-functions@ package. They are still available but marked as deprecated.

Changed in 0.10.0.1

  • @dct@ and @idct@ now have type @Vector Double -> Vector Double@

Changes in 0.10.0.0

  • The type classes Mean and Variance are split in two. This is required for distributions which do not have finite variance or mean.

  • The S.Sample.KernelDensity module 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 S.Sample.KernelDensity.Simple).

  • Histogram computation is added, in S.Sample.Histogram.

  • Discrete Fourie transform is added, in S.Transform

  • Root finding is added, in S.Math.RootFinding.

  • The complCumulative function is added to the Distribution class in order to accurately assess probalities P(X>x) which are used in one-tailed tests.

  • A stdDev function is added to the Variance class for distributions.

  • The constructor S.Distribution.normalDistr now takes standard deviation instead of variance as its parameter.

  • A bug in S.Quantile.weightedAvg is 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 mannWhitneyUCriticalValue is 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 mannWhitneyUSignificant is fixed. If either sample was larger than 20, it produced a completely incorrect answer.

  • One- and two-tailed tests in S.Tests.NonParametric are selected with sum types instead of Bool.

  • Test results returned as enumeration instead of @Bool@.

  • Performance improvements for Mann-Whitney U and Wilcoxon tests.

  • Module @S.Tests.NonParamtric@ is split into @S.Tests.MannWhitneyU@ and @S.Tests.WilcoxonT@

  • sortBy is added to S.Function.

  • 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.

  • Student-T, Fisher-Snedecor F-distributions and Cauchy-Lorentz distrbution are added.

  • The function S.Function.create is removed. Use generateM from the vector package instead.

  • Function to perform approximate comparion of doubles is added to S.Function.Comparison

  • Regularized incomplete beta function and its inverse are added to S.Function