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

Last updated: May 04,2024

1. Install "r-cran-lava" package

In this section, we are going to explain the necessary steps to install r-cran-lava on Kali Linux


    
        
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                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                r-cran-lava
            
                    
    
    Copied

2. Uninstall "r-cran-lava" package

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


    
        
            $
        

        
            
                sudo apt remove
            
                        
                r-cran-lava
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-lava
Version: 1.7.3+dfsg-1
Installed-Size: 2379
Maintainer: Debian R Packages Maintainers
Architecture: all
Depends: r-api-4.0, r-cran-future.apply, r-cran-numderiv, r-cran-progressr, r-cran-survival, r-cran-squarem
Recommends: r-cran-kernsmooth, r-cran-matrix, r-cran-data.table, r-cran-ellipse, r-cran-fields, r-cran-geepack, r-bioc-graph, r-cran-knitr, r-cran-bookdown, r-cran-rmarkdown, r-cran-igraph (>= 0.6), r-cran-lavasearch2, r-cran-lme4, r-cran-mets (>= 1.1), r-cran-nlme, r-cran-optimx, r-cran-polycor, r-cran-quantreg, r-cran-rgl, r-cran-r.rsp (>= 0.40), r-cran-testthat (>= 0.11), r-cran-zoo
Size: 2206876
SHA256: 10c419f060fb7fecd080e46ba1fcfc6556a5ad481b0d6b518364cb45ec0fc91d
SHA1: 8af3b99a442c7d06c83057392ca80870bd0b93dc
MD5sum: b2c2be057f14c6da4bb81684e8f36f63
Description: GNU R latent variable models
A general implementation of Structural Equation Models
with latent variables (MLE, 2SLS, and composite likelihood
estimators) with both continuous, censored, and ordinal
outcomes (Holst and Budtz-Joergensen (2013)
). The package also provides
methods for graph exploration (d-separation, back-door criterion),
simulation of general non-linear latent variable models, and
estimation of influence functions for a broad range of statistical
models.
Description-md5:
Homepage: https://cran.r-project.org/package=lava
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-lava/r-cran-lava_1.7.3+dfsg-1_all.deb