haskell-statistics 0.15.2.0-1build3 source package in Ubuntu

Changelog

haskell-statistics (0.15.2.0-1build3) groovy; urgency=medium

  * No-change rebuild for new GHC ABIs

 -- Steve Langasek <email address hidden>  Sat, 29 Aug 2020 18:55:30 +0000

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Uploaded by:
Steve Langasek on 2020-08-29
Uploaded to:
Groovy
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
haskell
Urgency:
Medium Urgency

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Series Pocket Published Component Section
Groovy release on 2020-09-09 universe haskell

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File Size SHA-256 Checksum
haskell-statistics_0.15.2.0.orig.tar.gz 96.1 KiB c496dbb8767a65ea3c352fd08ce1918200a0cc9d8f8b5f262aebbb43dee22a49
haskell-statistics_0.15.2.0-1build3.debian.tar.xz 3.9 KiB 4ae43f3b8153966b973f1564e6e0ceeb68a1167596cc4ea1207ed94418da9e9e
haskell-statistics_0.15.2.0-1build3.dsc 3.6 KiB d2266a1a102b6127daed488e91cff81c31c72d9d11aa5da74b93b512cedfe3e1

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Binary packages built by this source

libghc-statistics-dev: A library of statistical types, data, and functions

 This library provides a number of common functions and types useful
 in statistics. Our focus is 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 three broad categories:
 .
 Working with widely used discrete and continuous probability
 distributions. (There are dozens of exotic distributions in use; we
 focus on the most common.)
 .
 Computing with sample data: quantile estimation, kernel density
 estimation, bootstrap methods, regression and autocorrelation analysis.
 .
 Random variate generation under several different distributions.
 .
 This package provides a library for the Haskell programming language.
 See http://www.haskell.org/ for more information on Haskell.

libghc-statistics-doc: A library of statistical types, data, and functions; documentation

 This library provides a number of common functions and types useful
 in statistics. Our focus is 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 three broad categories:
 .
 Working with widely used discrete and continuous probability
 distributions. (There are dozens of exotic distributions in use; we
 focus on the most common.)
 .
 Computing with sample data: quantile estimation, kernel density
 estimation, bootstrap methods, and autocorrelation analysis.
 .
 Random variate generation under several different distributions.
 .
 This package provides the documentation for a library for the Haskell
 programming language.
 See http://www.haskell.org/ for more information on Haskell.

libghc-statistics-prof: A library of statistical types, data, and functions; profiling libraries

 This library provides a number of common functions and types useful
 in statistics. Our focus is 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 three broad categories:
 .
 Working with widely used discrete and continuous probability
 distributions. (There are dozens of exotic distributions in use; we
 focus on the most common.)
 .
 Computing with sample data: quantile estimation, kernel density
 estimation, bootstrap methods, and autocorrelation analysis.
 .
 Random variate generation under several different distributions.
 .
 This package provides a library for the Haskell programming language, compiled
 for profiling. See http://www.haskell.org/ for more information on Haskell.