How to Install and Uninstall libranlip-dev Package on Kali Linux

Last updated: November 22,2024

1. Install "libranlip-dev" package

Please follow the guidance below to install libranlip-dev on Kali Linux


    
        
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                sudo apt update
            
                    
    
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                sudo apt install
            
                        
                libranlip-dev
            
                    
    
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2. Uninstall "libranlip-dev" package

In this section, we are going to explain the necessary steps to uninstall libranlip-dev on Kali Linux:


    
        
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                sudo apt remove
            
                        
                libranlip-dev
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the libranlip-dev package on Kali Linux

Package: libranlip-dev
Source: libranlip
Version: 1.0-5
Installed-Size: 61
Maintainer: Debian QA Group
Architecture: amd64
Depends: libc6 (>= 2.14), libstdc++6 (>= 5), libtnt-dev, libranlip1c2 (= 1.0-5)
Size: 15316
SHA256: 6df75ebd4d7b82232c3137fc0e0c6480a560aefd085232f23055f763a6a0fe5f
SHA1: c61e524addcaa69b6beabbebb8555070c726d4ec
MD5sum: 0d72c3d0122db3f8d3a7dfb1a833c974
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: devel::library, role::devel-lib
Section: libdevel
Priority: optional
Filename: pool/main/libr/libranlip/libranlip-dev_1.0-5_amd64.deb