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| -rw-r--r-- | gnu/packages/haskell.scm | 59 |
1 files changed, 59 insertions, 0 deletions
diff --git a/gnu/packages/haskell.scm b/gnu/packages/haskell.scm index 490d61453a..b3cbe616be 100644 --- a/gnu/packages/haskell.scm +++ b/gnu/packages/haskell.scm @@ -9354,4 +9354,63 @@ implementation provides a work-stealing scheduler and supports forking tasks that are much lighter weight than IO-threads.") (license license:bsd-3))) +(define-public ghc-statistics + (package + (name "ghc-statistics") + (version "0.14.0.2") + (source + (origin + (method url-fetch) + (uri (string-append "https://hackage.haskell.org/package/" + "statistics-" version "/" + "statistics-" version ".tar.gz")) + (sha256 + (base32 + "0y27gafkib0x0fn39qfn2rkgsfrm09ng35sbb5dwr7rclhnxz59l")))) + (build-system haskell-build-system) + (inputs + `(("ghc-aeson" ,ghc-aeson) + ("ghc-base-orphans" ,ghc-base-orphans) + ("ghc-erf" ,ghc-erf) + ("ghc-math-functions" ,ghc-math-functions) + ("ghc-monad-par" ,ghc-monad-par) + ("ghc-mwc-random" ,ghc-mwc-random) + ("ghc-primitive" ,ghc-primitive) + ("ghc-vector" ,ghc-vector) + ("ghc-vector-algorithms" ,ghc-vector-algorithms) + ("ghc-vector-th-unbox" ,ghc-vector-th-unbox) + ("ghc-vector-binary-instances" ,ghc-vector-binary-instances))) + (native-inputs + `(("ghc-hunit" ,ghc-hunit) + ("ghc-quickcheck" ,ghc-quickcheck) + ("ghc-ieee754", ghc-ieee754) + ("ghc-test-framework" ,ghc-test-framework) + ("ghc-test-framework-hunit" ,ghc-test-framework-hunit) + ("ghc-test-framework-quickcheck2" ,ghc-test-framework-quickcheck2))) + (arguments + `(#:tests? #f)) ; FIXME: Test-Suite `spec` fails. + (home-page "https://github.com/bos/mwc-random") + (synopsis "Haskell library of statistical types, data, and functions") + (description "This library provides a number of common functions +and types useful in statistics. We focus on high performance, numerical +robustness, and use of good algorithms. Where possible, we provide references +to the statistical literature. + +The library's facilities can be divided into four broad categories: + +@itemize +@item Working with widely used discrete and continuous probability +distributions. (There are dozens of exotic distributions in use; we focus +on the most common.) + +@item Computing with sample data: quantile estimation, kernel density +estimation, histograms, bootstrap methods, significance testing, +and regression and autocorrelation analysis. + +@item Random variate generation under several different distributions. + +@item Common statistical tests for significant differences between samples. +@end itemize") + (license license:bsd-2))) + ;;; haskell.scm ends here |