## Changelog for statistics-0.14.0.0

## 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 droppedNew 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 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.

## 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