<commit_before>homepage: https://github.com/bos/statistics
changelog-type: markdown
hash: 10f674f0a5bf63b4e14e0d9186d35254bf5200003831f46a9c6a4493eaa57a20
test-bench-deps:
  test-framework-hunit: -any
  mwc-random: -any
  test-framework: -any
  base: -any
  test-framework-quickcheck2: -any
  HUnit: -any
  erf: -any
  math-functions: -any
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  statistics: -any
  vector-algorithms: -any
  QuickCheck: ! '>=2.7.5'
  aeson: -any
  primitive: -any
  vector: -any
maintainer: <NAME> <<EMAIL>>
synopsis: A library of statistical types, data, and functions
changelog: ! "## Changes in 0.14.0.0\n\nBreaking update. It seriously changes parts
  of API. It adds new data types for\ndealing with with estimates, confidence intervals,
  confidence levels and\np-value. Also API for statistical tests is changed.\n\n *
  Module `Statistis.Types` now contains new data types for estimates,\n   upper/lower
  bounds, confidence level, and p-value.\n\n\t- `CL` for representing confidence level\n\t-
  `PValue` for representing p-values\n\t- `Estimate` data type moved here from `Statistis.Resampling.Bootstrap`
  and\n      now parametrized by type of error.\n\t- `NormalError` — represents normal
  error.\n    - `ConfInt` — generic confidence interval\n    - `UpperLimit`,`LowerLimit`
  for upper/lower limits.\n\n * New API for statistical tests. Instead of simply return
  significant/not\n   significant it returns p-value, test statistics and distribution
  of test\n   statistics if it's available. Tests also return `Nothing` instead of
  throwing\n   error if sample size is not sufficient. Fixes #25.\n\n * `Statistics.Tests.Types.TestType`
  data type dropped\n\n * New smart constructors for distributions are added. They
  return `Nothing` if\n   parameters are outside of allowed range.\n\n * Serialization
  instances (`Show/Read, Binary, ToJSON/FromJSON`) for\n   distributions no longer
  allows to create data types with invalid\n   parameters. They will fail to parse.
  Cached values are not serialized either\n   so `Binary` instances changed normal
  and F-distributions.\n\n   Encoding to JSON changed for Normal, F-distribution,
  and χ²\n   distributions. However data created using older statistics will be\n
  \  successfully decoded.\n\n   Fixes #59.\n\n * Statistics.Resample.Bootstrap uses
  new data types for central estimates.\n\n * Function for calculation of confidence
  intervals for Poisson and binomial\n   distribution added in `Statistics.ConfidenceInt`\n\n
  * Tests of position now allow to ask whether first sample on average larger\n   than
  second, second larger than first or whether they differ significantly.\n   Affects
  Wilcoxon-T, Mann-Whitney-U, and Student-T tests.\n\n * API for bootstrap changed.
  New data types added.\n\n * Bug fixes for #74, #81, #83, #92, #94\n\n * `complCumulative`
  added for many distributions.\n\n\n\n## Changes in 0.13.3.0\n\n * Kernel density
  estimation and FFT use generic versions now.\n\n * Code for calculation of Spearman
  and Pearson correlation added. Modules\n   `Statistics.Correlation.Spearman` and
  `Statistics.Correlation.Pearson`.\n\n * Function for calculation covariance added
  in `Statistics.Sample`.\n\n * `Statistics.Function.pair` added. It zips vector and
  check that lengths are\n   equal.\n\n * New functions added to `Statistics.Matrix`\n\n
  * Laplace distribution added.\n\n\n## Changes in 0.13.2.3\n\n * Vector dependency
  restored to >=0.10\n\n\n## Changes in 0.13.2.2\n\n * Vector dependency lowered to
  >=0.9\n\n\n## Changes in 0.13.2.1\n\n * Vector dependency bumped to >=0.10\n\n\n##
  Changes in 0.13.2.0\n\n * Support for regression bootstrap added\n\n\n## Changes
  in 0.13.1.1\n\n * Fix for out of bound access in bootstrap (see `bos/criterion#52`)\n\n\n##
  Changes in 0.13.1.0\n\n  * All types now support JSON encoding and decoding.\n\n\n##
  Changes in 0.12.0.0\n\n  * The `Statistics.Math` module has been removed, after
  being\n    deprecated for several years.  Use the\n    [math-functions](http://hackage.haskell.org/package/math-functions)\n
  \   package instead.\n\n  * The `Statistics.Test.NonParametric` module has been
  removed, after\n    being deprecated for several years.\n\n  * Added support for
  Kendall's tau.\n\n  * Added support for OLS regression.\n\n  * Added basic 2D matrix
  support.\n\n  * Added the Kruskal-Wallis test.\n\n## Changes in 0.11.0.3\n\n  *
  Fixed a subtle bug in calculation of the jackknifed unbiased variance.\n\n  * The
  test suite now requires QuickCheck 2.7.\n\n  * We now calculate quantiles for normal
  distribution in a more\n    numerically stable way (bug #64).\n\n## Changes in 0.10.6.0\n\n
  \ * The Estimator type has become an algebraic data type.  This allows\n    the
  jackknife function to potentially use more efficient jackknife\n    implementations.\n\n
  \ * jackknifeMean, jackknifeStdDev, jackknifeVariance,\n    jackknifeVarianceUnb:
  new functions.  These have O(n) cost instead\n    of the O(n^2) cost of the standard
  jackknife.\n\n  * The mean function has been renamed to welfordMean; a new\n    implementation
  of mean has better numerical accuracy in almost all\n    cases.\n\n## Changes in
  0.10.5.2\n\n  * histogram correctly chooses range when all elements in the sample
  are same\n    (bug #57)\n\n\n## Changes in 0.10.5.1\n\n  * Bug fix for S.Distributions.Normal.standard
  introduced in 0.10.5.0 (Bug #56)\n\n\n## Changes in 0.10.5.0\n\n  * Enthropy type
  class for distributions is added.\n\n  * Probability and probability density of
  distribution is given in\n    log domain too.\n\n## Changes in 0.10.4.0\n\n  * Support
  for versions of GHC older than 7.2 is discontinued.\n\n  * All datatypes now support
  'Data.Binary' and 'GHC.Generics'.\n\n## Changes in 0.10.3.0\n\n  * Bug fixes\n\n##
  Changes in 0.10.2.0\n\n  * Bugs in DCT and IDCT are fixed.\n\n  * Accesors for uniform
  distribution are added.\n\n  * ContGen instances for all continous distribtuions
  are added.\n\n  * Beta distribution is added.\n\n  * Constructor for improper gamma
  distribtuion is added.\n\n  * Binomial distribution allows zero trials.\n\n  * Poisson
  distribution now accept zero parameter.\n\n  * Integer overflow in caculation of
  Wilcoxon-T test is fixed.\n\n  * Bug in 'ContGen' instance for normal distribution
  is fixed.\n\n## Changes in 0.10.1.0\n\n  * Kolmogorov-Smirnov nonparametric test
  added.\n\n  * Pearson chi squared test added.\n\n  * Type class for generating random
  variates for given distribution\n    is added.\n\n  * Modules 'Statistics.Math'
  and 'Statistics.Constants' are moved to\n    the `math-functions` package. They
  are still available but marked\n    as deprecated.\n\n\n## Changes in 0.10.0.1\n\n
  \ * `dct` and `idct` now have type `Vector Double -> Vector Double`\n\n\n## Changes
  in 0.10.0.0\n\n  * The type classes Mean and Variance are split in two. This is\n
  \   required for distributions which do not have finite variance or\n    mean.\n\n
  \ * The S.Sample.KernelDensity module has been renamed, and\n    completely rewritten
  to be much more robust.  The older module\n    oversmoothed multi-modal data.  (The
  older module is still\n    available under the name S.Sample.KernelDensity.Simple).\n\n
  \ * Histogram computation is added, in S.Sample.Histogram.\n\n  * Discrete Fourie
  transform is added, in S.Transform\n\n  * Root finding is added, in S.Math.RootFinding.\n\n
  \ * The complCumulative function is added to the Distribution\n    class in order
  to accurately assess probalities P(X>x) which are\n    used in one-tailed tests.\n\n
  \ * A stdDev function is added to the Variance class for\n    distributions.\n\n
  \ * The constructor S.Distribution.normalDistr now takes standard\n    deviation
  instead of variance as its parameter.\n\n  * A bug in S.Quantile.weightedAvg is
  fixed. It produced a wrong\n    answer if a sample contained only one element.\n\n
  \ * Bugs in quantile estimations for chi-square and gamma distribution\n    are
  fixed.\n\n  * Integer overlow in mannWhitneyUCriticalValue is fixed. It\n    produced
  incorrect critical values for moderately large\n    samples. Something around 20
  for 32-bit machines and 40 for 64-bit\n    ones.\n\n  * A bug in mannWhitneyUSignificant
  is fixed. If either sample was\n    larger than 20, it produced a completely incorrect
  answer.\n\n  * One- and two-tailed tests in S.Tests.NonParametric are selected\n
  \   with sum types instead of Bool.\n\n  * Test results returned as enumeration
  instead of `Bool`.\n\n  * Performance improvements for Mann-Whitney U and Wilcoxon
  tests.\n\n  * Module `S.Tests.NonParamtric` is split into `S.Tests.MannWhitneyU`\n
  \   and `S.Tests.WilcoxonT`\n\n  * sortBy is added to S.Function.\n\n  * Mean and
  variance for gamma distribution are fixed.\n\n  * Much faster cumulative probablity
  functions for Poisson and\n    hypergeometric distributions.\n\n  * Better density
  functions for gamma and Poisson distributions.\n\n  * Student-T, Fisher-Snedecor
  F-distributions and Cauchy-Lorentz\n    distrbution are added.\n\n  * The function
  S.Function.create is removed. Use generateM from\n    the vector package instead.\n\n
  \ * Function to perform approximate comparion of doubles is added to\n    S.Function.Comparison\n\n
  \ * Regularized incomplete beta function and its inverse are added to\n    S.Function\n"
basic-deps:
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  monad-par: ! '>=0.3.4'
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  math-functions: ! '>=0.1.7'
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  deepseq: ! '>=1.1.0.2'
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  primitive: ! '>=0.3'
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all-versions:
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- '0.2.2'
- '0.3'
- '0.3.1'
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- '0.5.0.0'<commit_msg>Update from Hackage at 2017-05-11T20:54:31Z<commit_after>homepage: https://github.com/bos/statistics
changelog-type: markdown
hash: 6432ecb4f7824f517b3ad2f8195b8554cb373621a26a72f4b511bdb5099a145c
test-bench-deps:
  test-framework-hunit: -any
  mwc-random: -any
  test-framework: -any
  base: -any
  test-framework-quickcheck2: -any
  HUnit: -any
  erf: -any
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  ieee754: ! '>=0.7.3'
  statistics: -any
  vector-algorithms: -any
  QuickCheck: ! '>=2.7.5'
  aeson: -any
  primitive: -any
  vector: -any
maintainer: <NAME> <<EMAIL>>
synopsis: A library of statistical types, data, and functions
changelog: ! "## Changes in 0.14.0.0\n\nBreaking update. It seriously changes parts
  of API. It adds new data types for\ndealing with with estimates, confidence intervals,
  confidence levels and\np-value. Also API for statistical tests is changed.\n\n *
  Module `Statistis.Types` now contains new data types for estimates,\n   upper/lower
  bounds, confidence level, and p-value.\n\n\t- `CL` for representing confidence level\n\t-
  `PValue` for representing p-values\n\t- `Estimate` data type moved here from `Statistis.Resampling.Bootstrap`
  and\n      now parametrized by type of error.\n\t- `NormalError` — represents normal
  error.\n    - `ConfInt` — generic confidence interval\n    - `UpperLimit`,`LowerLimit`
  for upper/lower limits.\n\n * New API for statistical tests. Instead of simply return
  significant/not\n   significant it returns p-value, test statistics and distribution
  of test\n   statistics if it's available. Tests also return `Nothing` instead of
  throwing\n   error if sample size is not sufficient. Fixes #25.\n\n * `Statistics.Tests.Types.TestType`
  data type dropped\n\n * New smart constructors for distributions are added. They
  return `Nothing` if\n   parameters are outside of allowed range.\n\n * Serialization
  instances (`Show/Read, Binary, ToJSON/FromJSON`) for\n   distributions no longer
  allows to create data types with invalid\n   parameters. They will fail to parse.
  Cached values are not serialized either\n   so `Binary` instances changed normal
  and F-distributions.\n\n   Encoding to JSON changed for Normal, F-distribution,
  and χ²\n   distributions. However data created using older statistics will be\n
  \  successfully decoded.\n\n   Fixes #59.\n\n * Statistics.Resample.Bootstrap uses
  new data types for central estimates.\n\n * Function for calculation of confidence
  intervals for Poisson and binomial\n   distribution added in `Statistics.ConfidenceInt`\n\n
  * Tests of position now allow to ask whether first sample on average larger\n   than
  second, second larger than first or whether they differ significantly.\n   Affects
  Wilcoxon-T, Mann-Whitney-U, and Student-T tests.\n\n * API for bootstrap changed.
  New data types added.\n\n * Bug fixes for #74, #81, #83, #92, #94\n\n * `complCumulative`
  added for many distributions.\n\n\n\n## Changes in 0.13.3.0\n\n * Kernel density
  estimation and FFT use generic versions now.\n\n * Code for calculation of Spearman
  and Pearson correlation added. Modules\n   `Statistics.Correlation.Spearman` and
  `Statistics.Correlation.Pearson`.\n\n * Function for calculation covariance added
  in `Statistics.Sample`.\n\n * `Statistics.Function.pair` added. It zips vector and
  check that lengths are\n   equal.\n\n * New functions added to `Statistics.Matrix`\n\n
  * Laplace distribution added.\n\n\n## Changes in 0.13.2.3\n\n * Vector dependency
  restored to >=0.10\n\n\n## Changes in 0.13.2.2\n\n * Vector dependency lowered to
  >=0.9\n\n\n## Changes in 0.13.2.1\n\n * Vector dependency bumped to >=0.10\n\n\n##
  Changes in 0.13.2.0\n\n * Support for regression bootstrap added\n\n\n## Changes
  in 0.13.1.1\n\n * Fix for out of bound access in bootstrap (see `bos/criterion#52`)\n\n\n##
  Changes in 0.13.1.0\n\n  * All types now support JSON encoding and decoding.\n\n\n##
  Changes in 0.12.0.0\n\n  * The `Statistics.Math` module has been removed, after
  being\n    deprecated for several years.  Use the\n    [math-functions](http://hackage.haskell.org/package/math-functions)\n
  \   package instead.\n\n  * The `Statistics.Test.NonParametric` module has been
  removed, after\n    being deprecated for several years.\n\n  * Added support for
  Kendall's tau.\n\n  * Added support for OLS regression.\n\n  * Added basic 2D matrix
  support.\n\n  * Added the Kruskal-Wallis test.\n\n## Changes in 0.11.0.3\n\n  *
  Fixed a subtle bug in calculation of the jackknifed unbiased variance.\n\n  * The
  test suite now requires QuickCheck 2.7.\n\n  * We now calculate quantiles for normal
  distribution in a more\n    numerically stable way (bug #64).\n\n## Changes in 0.10.6.0\n\n
  \ * The Estimator type has become an algebraic data type.  This allows\n    the
  jackknife function to potentially use more efficient jackknife\n    implementations.\n\n
  \ * jackknifeMean, jackknifeStdDev, jackknifeVariance,\n    jackknifeVarianceUnb:
  new functions.  These have O(n) cost instead\n    of the O(n^2) cost of the standard
  jackknife.\n\n  * The mean function has been renamed to welfordMean; a new\n    implementation
  of mean has better numerical accuracy in almost all\n    cases.\n\n## Changes in
  0.10.5.2\n\n  * histogram correctly chooses range when all elements in the sample
  are same\n    (bug #57)\n\n\n## Changes in 0.10.5.1\n\n  * Bug fix for S.Distributions.Normal.standard
  introduced in 0.10.5.0 (Bug #56)\n\n\n## Changes in 0.10.5.0\n\n  * Enthropy type
  class for distributions is added.\n\n  * Probability and probability density of
  distribution is given in\n    log domain too.\n\n## Changes in 0.10.4.0\n\n  * Support
  for versions of GHC older than 7.2 is discontinued.\n\n  * All datatypes now support
  'Data.Binary' and 'GHC.Generics'.\n\n## Changes in 0.10.3.0\n\n  * Bug fixes\n\n##
  Changes in 0.10.2.0\n\n  * Bugs in DCT and IDCT are fixed.\n\n  * Accesors for uniform
  distribution are added.\n\n  * ContGen instances for all continous distribtuions
  are added.\n\n  * Beta distribution is added.\n\n  * Constructor for improper gamma
  distribtuion is added.\n\n  * Binomial distribution allows zero trials.\n\n  * Poisson
  distribution now accept zero parameter.\n\n  * Integer overflow in caculation of
  Wilcoxon-T test is fixed.\n\n  * Bug in 'ContGen' instance for normal distribution
  is fixed.\n\n## Changes in 0.10.1.0\n\n  * Kolmogorov-Smirnov nonparametric test
  added.\n\n  * Pearson chi squared test added.\n\n  * Type class for generating random
  variates for given distribution\n    is added.\n\n  * Modules 'Statistics.Math'
  and 'Statistics.Constants' are moved to\n    the `math-functions` package. They
  are still available but marked\n    as deprecated.\n\n\n## Changes in 0.10.0.1\n\n
  \ * `dct` and `idct` now have type `Vector Double -> Vector Double`\n\n\n## Changes
  in 0.10.0.0\n\n  * The type classes Mean and Variance are split in two. This is\n
  \   required for distributions which do not have finite variance or\n    mean.\n\n
  \ * The S.Sample.KernelDensity module has been renamed, and\n    completely rewritten
  to be much more robust.  The older module\n    oversmoothed multi-modal data.  (The
  older module is still\n    available under the name S.Sample.KernelDensity.Simple).\n\n
  \ * Histogram computation is added, in S.Sample.Histogram.\n\n  * Discrete Fourie
  transform is added, in S.Transform\n\n  * Root finding is added, in S.Math.RootFinding.\n\n
  \ * The complCumulative function is added to the Distribution\n    class in order
  to accurately assess probalities P(X>x) which are\n    used in one-tailed tests.\n\n
  \ * A stdDev function is added to the Variance class for\n    distributions.\n\n
  \ * The constructor S.Distribution.normalDistr now takes standard\n    deviation
  instead of variance as its parameter.\n\n  * A bug in S.Quantile.weightedAvg is
  fixed. It produced a wrong\n    answer if a sample contained only one element.\n\n
  \ * Bugs in quantile estimations for chi-square and gamma distribution\n    are
  fixed.\n\n  * Integer overlow in mannWhitneyUCriticalValue is fixed. It\n    produced
  incorrect critical values for moderately large\n    samples. Something around 20
  for 32-bit machines and 40 for 64-bit\n    ones.\n\n  * A bug in mannWhitneyUSignificant
  is fixed. If either sample was\n    larger than 20, it produced a completely incorrect
  answer.\n\n  * One- and two-tailed tests in S.Tests.NonParametric are selected\n
  \   with sum types instead of Bool.\n\n  * Test results returned as enumeration
  instead of `Bool`.\n\n  * Performance improvements for Mann-Whitney U and Wilcoxon
  tests.\n\n  * Module `S.Tests.NonParamtric` is split into `S.Tests.MannWhitneyU`\n
  \   and `S.Tests.WilcoxonT`\n\n  * sortBy is added to S.Function.\n\n  * Mean and
  variance for gamma distribution are fixed.\n\n  * Much faster cumulative probablity
  functions for Poisson and\n    hypergeometric distributions.\n\n  * Better density
  functions for gamma and Poisson distributions.\n\n  * Student-T, Fisher-Snedecor
  F-distributions and Cauchy-Lorentz\n    distrbution are added.\n\n  * The function
  S.Function.create is removed. Use generateM from\n    the vector package instead.\n\n
  \ * Function to perform approximate comparion of doubles is added to\n    S.Function.Comparison\n\n
  \ * Regularized incomplete beta function and its inverse are added to\n    S.Function\n"
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