statistics-0.16.0.2: changelog.md
## Changes in 0.16.0.2
* Bug in constructor of binomial distribution is fixed (#181). It accepted
out-of range probability before.
## 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](http://hackage.haskell.org/package/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