How to Install and Uninstall r-cran-mixsqp Package on Kali Linux

Last updated: May 19,2024

1. Install "r-cran-mixsqp" package

Learn how to install r-cran-mixsqp on Kali Linux


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-mixsqp
            
                    
    
    Copied

2. Uninstall "r-cran-mixsqp" package

This is a short guide on how to uninstall r-cran-mixsqp on Kali Linux:


    
        
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                sudo apt remove
            
                        
                r-cran-mixsqp
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

3. Information about the r-cran-mixsqp package on Kali Linux

Package: r-cran-mixsqp
Version: 0.3-54-1
Installed-Size: 509
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-cran-irlba, r-cran-rcpp (>= 0.12.15), r-cran-rcpparmadillo, libblas3 | libblas.so.3, libc6 (>= 2.29), libgcc-s1 (>= 3.0), liblapack3 | liblapack.so.3, libstdc++6 (>= 13.1)
Recommends: r-cran-testthat, r-cran-knitr, r-cran-rmarkdown
Size: 307600
SHA256: cd0fb73df1b4dce027ee126b62978592a44541b4919aaeb7dd14a3da3d523474
SHA1: 351f29c82128af3e96a101c8a8af9e9e8c3e4b11
MD5sum: da4aea313dfc147b923454fccb94a8b0
Description: Quadratic Programming for Estimation of Mixture Proportions
Provides an optimization method based on sequential
quadratic programming (SQP) for maximum likelihood estimation of
the mixture proportions in a finite mixture model where the
component densities are known. The algorithm is expected to obtain
solutions that are at least as accurate as the state-of-the-art
MOSEK interior-point solver (called by function "KWDual" in the
'REBayes' package), and they are expected to arrive at solutions
more quickly when the number of samples is large and the number of
mixture components is not too large. This implements the "mix-SQP"
algorithm, with some improvements, described in Y. Kim,
P. Carbonetto, M. Stephens & M. Anitescu (2020)
.
Description-md5:
Homepage: https://cran.r-project.org/package=mixsqp
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-mixsqp/r-cran-mixsqp_0.3-54-1_amd64.deb