haskell-statistics 0.13.3.0-3build6 source package in Ubuntu

Changelog

haskell-statistics (0.13.3.0-3build6) bionic; urgency=medium

  * No-change rebuild for new GHC ABIs

 -- Steve Langasek <email address hidden>  Sun, 05 Nov 2017 03:39:22 +0000

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Uploaded by:
Steve Langasek
Uploaded to:
Bionic
Original maintainer:
Ubuntu Developers
Architectures:
any all
Section:
haskell
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Bionic release universe haskell

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File Size SHA-256 Checksum
haskell-statistics_0.13.3.0.orig.tar.gz 81.6 KiB 6e7fe0f10086725c696fdd855caf4b6fb58ca5100bd0c9995f575f5b071381ed
haskell-statistics_0.13.3.0-3build6.debian.tar.xz 3.6 KiB 92825323ffda61add2e68f9b4987d60bcde7990c1459304ff2be783af5cd2eb1
haskell-statistics_0.13.3.0-3build6.dsc 3.1 KiB 2e4c47161c07dc4667eb763acf1d832c7bc11f30cc395844173377b33399e921

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Binary packages built by this source

libghc-statistics-dev: No summary available for libghc-statistics-dev in ubuntu cosmic.

No description available for libghc-statistics-dev in ubuntu cosmic.

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.