Changelog of @hackage/statistics 0.16.0.0

Changes in 0.16.0.0

  • Random number generation switched to API introduced in random-1.2

  • Support of GHC<7.10 is dropped

  • Fix for chi-squared test (#167) which was completely wrong

  • Computation of CDF and quantiles of Cauchy distribution is now numerically stable.

  • Fix loss of precision in computing of CDF of gamma distribution

  • Log-normal and Weibull distributions added.

  • DiscreteGen instance added for DiscreteUniform

Changes in 0.15.2.0

  • Test suite is finally fixed (#42, #123). It took very-very-very long time but finally happened.

  • Avoid loss of precision when computing CDF for exponential districution.

  • Avoid loss of precision when computing CDF for geometric districution. Add complement of CDF.

  • Correctly handle case of n=0 in poissonCI

Changes in 0.15.1.1

  • Fix build for GHC8.0 & 7.10

Changes in 0.15.1.0

  • GHCJS support

  • Concurrent resampling now uses async instead of hand-rolled primitives

Changes in 0.15.0.0

  • Modules Statistics.Matrix.* are split into new package dense-linear-algebra and exponent field is removed from Matrix data type.

  • Module Statistics.Normalize which contains functions for normalization of samples

  • Module Statistics.Quantile reworked:

    • ContParam given Default instance
    • quantile should be used instead of continuousBy
    • median and mad are added
    • quantiles and quantilesVec functions for computation of set of quantiles added.

  • Modules Statistics.Function.Comparison and Statistics.Math.RootFinding are removed. Corresponding functionality could be found in math-functions package.

  • Fix vector index out of bounds in bootstrapBCA and bootstrapRegress (see issue #149)

Changes in 0.14.0.2

  • Compatibility fixes with older GHC

Changes in 0.14.0.1

  • Restored compatibility with GHC 7.4 & 7.6

Changes in 0.14.0.0

Breaking update. It seriously changes parts of API. It adds new data types for dealing with with estimates, confidence intervals, confidence levels and p-value. Also API for statistical tests is changed.

  • Module Statistis.Types now contains new data types for estimates, upper/lower bounds, confidence level, and p-value.

    • CL for representing confidence level
    • PValue for representing p-values
    • Estimate data type moved here from Statistis.Resampling.Bootstrap and now parametrized by type of error.
    • NormalError — represents normal error.
    • ConfInt — generic confidence interval
    • UpperLimit,LowerLimit for upper/lower limits.

  • New API for statistical tests. Instead of simply return significant/not significant it returns p-value, test statistics and distribution of test statistics if it's available. Tests also return Nothing instead of throwing error if sample size is not sufficient. Fixes #25.

  • Statistics.Tests.Types.TestType data type dropped

  • New smart constructors for distributions are added. They return Nothing if parameters are outside of allowed range.

  • Serialization instances (Show/Read, Binary, ToJSON/FromJSON) for distributions no longer allows to create data types with invalid parameters. They will fail to parse. Cached values are not serialized either so Binary instances changed normal and F-distributions.

    Encoding to JSON changed for Normal, F-distribution, and χ² distributions. However data created using older statistics will be successfully decoded.

    Fixes #59.

  • Statistics.Resample.Bootstrap uses new data types for central estimates.

  • Function for calculation of confidence intervals for Poisson and binomial distribution added in Statistics.ConfidenceInt

  • Tests of position now allow to ask whether first sample on average larger than second, second larger than first or whether they differ significantly. Affects Wilcoxon-T, Mann-Whitney-U, and Student-T tests.

  • API for bootstrap changed. New data types added.

  • Bug fixes for #74, #81, #83, #92, #94

  • complCumulative added for many distributions.

Changes in 0.13.3.0

  • Kernel density estimation and FFT use generic versions now.

  • Code for calculation of Spearman and Pearson correlation added. Modules Statistics.Correlation.Spearman and Statistics.Correlation.Pearson.

  • Function for calculation covariance added in Statistics.Sample.

  • Statistics.Function.pair added. It zips vector and check that lengths are equal.

  • New functions added to Statistics.Matrix

  • Laplace distribution added.

Changes in 0.13.2.3

  • Vector dependency restored to >=0.10

Changes in 0.13.2.2

  • Vector dependency lowered to >=0.9

Changes in 0.13.2.1

  • Vector dependency bumped to >=0.10

Changes in 0.13.2.0

  • Support for regression bootstrap added

Changes in 0.13.1.1

  • Fix for out of bound access in bootstrap (see bos/criterion#52)

Changes in 0.13.1.0

  • All types now support JSON encoding and decoding.

Changes in 0.12.0.0

  • The Statistics.Math module has been removed, after being deprecated for several years. Use the math-functions package instead.

  • The Statistics.Test.NonParametric module has been removed, after being deprecated for several years.

  • Added support for Kendall's tau.

  • Added support for OLS regression.

  • Added basic 2D matrix support.

  • Added the Kruskal-Wallis test.

Changes in 0.11.0.3

  • Fixed a subtle bug in calculation of the jackknifed unbiased variance.

  • The test suite now requires QuickCheck 2.7.

  • We now calculate quantiles for normal distribution in a more numerically stable way (bug #64).

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 continuous 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.

Changes 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