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

Last updated: November 07,2024

1. Install "r-cran-spatstat" package

Please follow the instructions below to install r-cran-spatstat on Kali Linux


    
        
            $
        

        
            
                sudo apt update
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt install
            
                        
                r-cran-spatstat
            
                    
    
    Copied

2. Uninstall "r-cran-spatstat" package

Please follow the guidance below to uninstall r-cran-spatstat on Kali Linux:


    
        
            $
        

        
            
                sudo apt remove
            
                        
                r-cran-spatstat
            
                    
    
    Copied


    
        
            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
    Copied

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

Package: r-cran-spatstat
Version: 3.0-7-1
Installed-Size: 5342
Maintainer: Debian R Packages Maintainers
Architecture: amd64
Depends: r-api-4.0, r-cran-spatstat.data (>= 3.0-1), r-cran-spatstat.geom (>= 3.2-7), r-cran-spatstat.random (>= 3.2-1), r-cran-spatstat.explore (>= 3.2-5), r-cran-spatstat.model (>= 3.2-8), r-cran-spatstat.linnet (>= 3.1-3), r-cran-spatstat.utils (>= 3.0-3)
Size: 3796744
SHA256: 4823e2c9de91f80e3cdb622c39f2f42b93c2b52ccca77d36035d0d06c3af2ee7
SHA1: 7b2dd2c308b753d7e1e7f9c1724f5134b4352137
MD5sum: 354b57d02c7366d2cfa63048b649e890
Description: GNU R Spatial Point Pattern analysis, model-fitting, simulation, tests
A GNU R package for analysing spatial data, mainly Spatial Point Patterns,
including multitype/marked points and spatial covariates, in any
two-dimensional spatial region. Contains functions for plotting spatial
data, exploratory data analysis, model-fitting, simulation, spatial sampling,
model diagnostics, and formal inference. Data types include point patterns,
line segment patterns, spatial windows, and pixel images. Point process
models can be fitted to point pattern data. Cluster type models are fitted
by the method of minimum contrast. Very general Gibbs point process models
can be fitted to point pattern data using a function ppm similar to lm or glm.
Models may include dependence on covariates, interpoint interaction and
dependence on marks. Fitted models can be simulated automatically. Also
provides facilities for formal inference (such as chi-squared tests) and model
diagnostics (including simulation envelopes, residuals, residual plots and Q-Q
plots).
Description-md5:
Homepage: https://cran.r-project.org/package=spatstat
Section: gnu-r
Priority: optional
Filename: pool/main/r/r-cran-spatstat/r-cran-spatstat_3.0-7-1_amd64.deb