How to Install and Uninstall ghc-statistics Package on openSUSE Leap
Last updated: November 23,2024
1. Install "ghc-statistics" package
This guide let you learn how to install ghc-statistics on openSUSE Leap
$
sudo zypper refresh
Copied
$
sudo zypper install
ghc-statistics
Copied
2. Uninstall "ghc-statistics" package
This is a short guide on how to uninstall ghc-statistics on openSUSE Leap:
$
sudo zypper remove
ghc-statistics
Copied
3. Information about the ghc-statistics package on openSUSE Leap
Information for package ghc-statistics:
---------------------------------------
Repository : Main Repository
Name : ghc-statistics
Version : 0.16.0.1-bp155.2.14
Arch : x86_64
Vendor : openSUSE
Installed Size : 4.7 MiB
Installed : No
Status : not installed
Source package : ghc-statistics-0.16.0.1-bp155.2.14.src
Upstream URL : https://hackage.haskell.org/package/statistics
Summary : A 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:
* 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,
histograms, bootstrap methods, significance testing, and regression and
autocorrelation analysis.
* Random variate generation under several different distributions.
* Common statistical tests for significant differences between samples.
---------------------------------------
Repository : Main Repository
Name : ghc-statistics
Version : 0.16.0.1-bp155.2.14
Arch : x86_64
Vendor : openSUSE
Installed Size : 4.7 MiB
Installed : No
Status : not installed
Source package : ghc-statistics-0.16.0.1-bp155.2.14.src
Upstream URL : https://hackage.haskell.org/package/statistics
Summary : A 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:
* 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,
histograms, bootstrap methods, significance testing, and regression and
autocorrelation analysis.
* Random variate generation under several different distributions.
* Common statistical tests for significant differences between samples.