How to Install and Uninstall libranlip1c2 Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 17,2024

1. Install "libranlip1c2" package

Here is a brief guide to show you how to install libranlip1c2 on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install libranlip1c2

2. Uninstall "libranlip1c2" package

This guide let you learn how to uninstall libranlip1c2 on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove libranlip1c2 $ sudo apt autoclean && sudo apt autoremove

3. Information about the libranlip1c2 package on Ubuntu 21.10 (Impish Indri)

Package: libranlip1c2
Architecture: amd64
Version: 1.0-4.2build1
Priority: optional
Section: universe/libs
Source: libranlip
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Juan Esteban Monsalve Tobon
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 134
Depends: libc6 (>= 2.7), libstdc++6 (>= 5)
Conflicts: libranlip1
Filename: pool/universe/libr/libranlip/libranlip1c2_1.0-4.2build1_amd64.deb
Size: 105044
MD5sum: 5debb1950db1bdb7764b352dbaaa3abb
SHA1: b5a02012ce39f4e42326456bcde70cd190e01406
SHA256: 98fe16f2859105e61c6e51a020086cc7e5a3ffa4b22add7956aa53e2c153f43d
SHA512: 798a1d6fe2f286266ac435c09fe3e032b6fdad232ed81607f0abdfaeca154abb624e986d2bae8c834ea0dd3402ac742938a74747066ff40771253fb4cb8c9c12
Homepage: http://www.deakin.edu.au/~gleb/ranlip.html
Description-en: generates random variates with multivariate Lipschitz density
RanLip generates random variates with an arbitrary multivariate
Lipschitz density.
.
While generation of random numbers from a variety of distributions is
implemented in many packages (like GSL library
http://www.gnu.org/software/gsl/ and UNURAN library
http://statistik.wu-wien.ac.at/unuran/), generation of random variate
with an arbitrary distribution, especially in the multivariate case, is
a very challenging task. RanLip is a method of generation of random
variates with arbitrary Lipschitz-continuous densities, which works in
the univariate and multivariate cases, if the dimension is not very
large (say 3-10 variables).
.
Lipschitz condition implies that the rate of change of the function (in
this case, probability density p(x)) is bounded:
.
|p(x)-p(y)| .
From this condition, we can build an overestimate of the density, so
called hat function h(x)>=p(x), using a number of values of p(x) at some
points. The more values we use, the better is the hat function. The
method of acceptance/rejection then works as follows: generatea random
variate X with density h(x); generate an independent uniform on (0,1)
random number Z; if p(X)<=Z h(X), then return X, otherwise repeat all
the above steps.
.
RanLip constructs a piecewise constant hat function of the required
density p(x) by subdividing the domain of p (an n-dimensional rectangle)
into many smaller rectangles, and computes the upper bound on p(x)
within each of these rectangles, and uses this upper bound as the value
of the hat function.
Description-md5: 16e6dead1c9f1967dcaf2f4e023985e2