How to Install and Uninstall libranlip-dev Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: May 16,2024

1. Install "libranlip-dev" package

This is a short guide on how to install libranlip-dev on Ubuntu 16.04 LTS (Xenial Xerus)

$ sudo apt update $ sudo apt install libranlip-dev

2. Uninstall "libranlip-dev" package

Please follow the guidance below to uninstall libranlip-dev on Ubuntu 16.04 LTS (Xenial Xerus):

$ sudo apt remove libranlip-dev $ sudo apt autoclean && sudo apt autoremove

3. Information about the libranlip-dev package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: libranlip-dev
Priority: optional
Section: universe/libdevel
Installed-Size: 61
Maintainer: Ubuntu Developers
Original-Maintainer: Juan Esteban Monsalve Tobon
Architecture: amd64
Source: libranlip
Version: 1.0-4.2
Depends: libc6 (>= 2.4), libstdc++6 (>= 4.1.1), libtnt-dev, libranlip1c2 (= 1.0-4.2)
Filename: pool/universe/libr/libranlip/libranlip-dev_1.0-4.2_amd64.deb
Size: 15064
MD5sum: e2bf64ccc2fa7f370150d29a2c448c05
SHA1: 9c9eadddc5a84e9fe4f89534da7c9796a4dc2b9c
SHA256: b21494cf5a88a7565dad532bd43e6738ba499123e499602ca53aa640f5cc5a56
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
Homepage: http://www.deakin.edu.au/~gleb/ranlip.html
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu