How to Install and Uninstall libranlip1c2 Package on Kali Linux

Last updated: May 15,2024

1. Install "libranlip1c2" package

This guide let you learn how to install libranlip1c2 on Kali Linux

$ sudo apt update $ sudo apt install libranlip1c2

2. Uninstall "libranlip1c2" package

Please follow the steps below to uninstall libranlip1c2 on Kali Linux:

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

3. Information about the libranlip1c2 package on Kali Linux

Package: libranlip1c2
Source: libranlip
Version: 1.0-5
Installed-Size: 134
Maintainer: Debian QA Group
Architecture: amd64
Depends: libc6 (>= 2.14), libstdc++6 (>= 5)
Conflicts: libranlip1
Size: 105300
SHA256: d2ed4666fb70c95d2f6e03832cdfb5329cc2064184a2fa731105b7f0b98ee172
SHA1: 1c6b063e0fec81cf2a6542ac52eed4a10dcda1a1
MD5sum: d537eba64b6633b3c20f5fe1b580fd47
Description: 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:
Homepage: http://www.deakin.edu.au/~gleb/ranlip.html
Tag: role::shared-lib
Section: libs
Priority: optional
Filename: pool/main/libr/libranlip/libranlip1c2_1.0-5_amd64.deb