How to Install and Uninstall libghc-statistics-doc Package on Ubuntu 21.04 (Hirsute Hippo)

Last updated: May 18,2024

1. Install "libghc-statistics-doc" package

Please follow the instructions below to install libghc-statistics-doc on Ubuntu 21.04 (Hirsute Hippo)

$ sudo apt update $ sudo apt install libghc-statistics-doc

2. Uninstall "libghc-statistics-doc" package

Please follow the guidelines below to uninstall libghc-statistics-doc on Ubuntu 21.04 (Hirsute Hippo):

$ sudo apt remove libghc-statistics-doc $ sudo apt autoclean && sudo apt autoremove

3. Information about the libghc-statistics-doc package on Ubuntu 21.04 (Hirsute Hippo)

Package: libghc-statistics-doc
Architecture: all
Version: 0.15.2.0-1build4
Priority: extra
Section: universe/doc
Source: haskell-statistics
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Haskell Group
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 6621
Depends: haddock-interface-35
Recommends: libghc-aeson-doc, libghc-data-default-class-doc, libghc-dense-linear-algebra-doc, libghc-math-functions-doc, libghc-monad-par-doc, libghc-mwc-random-doc, libghc-primitive-doc, libghc-vector-algorithms-doc, libjs-mathjax
Filename: pool/universe/h/haskell-statistics/libghc-statistics-doc_0.15.2.0-1build4_all.deb
Size: 311804
MD5sum: 149ba4f0d31afdfcfc2a151f589ee070
SHA1: 0592abed1742fd16eb369690f023f1b0849d5f95
SHA256: 1b0c432c6a4563a829439f5f9bca90d2a68811dda15350163bbbd56c7b693fb4
SHA512: 9073893b6b210f3060de2dbdf64773a25e54bb0da0a1e288be9745e48fc1d1013aac75ea9d9f09814402e3188b9b1b837f1cd88d97564ec15f1c02d76a18a172
Homepage: https://github.com/bos/statistics
Description-en: 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.
Description-md5: c02e66a35d02ee578723b8968d648a4f