How to Install and Uninstall r-cran-spatstat Package on Ubuntu 16.04 LTS (Xenial Xerus)

Last updated: December 23,2024

1. Install "r-cran-spatstat" package

This guide covers the steps necessary to install r-cran-spatstat on Ubuntu 16.04 LTS (Xenial Xerus)


    
        
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                sudo apt update
            
                    
    
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            $
        

        
            
                sudo apt install
            
                        
                r-cran-spatstat
            
                    
    
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2. Uninstall "r-cran-spatstat" package

This is a short guide on how to uninstall r-cran-spatstat on Ubuntu 16.04 LTS (Xenial Xerus):


    
        
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                sudo apt remove
            
                        
                r-cran-spatstat
            
                    
    
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            $
        

        
            
                sudo apt autoclean && sudo apt autoremove
            
                    
    
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3. Information about the r-cran-spatstat package on Ubuntu 16.04 LTS (Xenial Xerus)

Package: r-cran-spatstat
Priority: optional
Section: universe/gnu-r
Installed-Size: 12133
Maintainer: Ubuntu Developers
Original-Maintainer: Debian Science Team
Architecture: amd64
Version: 1.37-0-1ubuntu1
Depends: libc6 (>= 2.4), libstdc++6 (>= 4.1.1), r-base-core (>= 3.1.2-1), r-cran-mgcv, r-cran-deldir, r-cran-abind, r-cran-tensor, r-cran-polyclip (>= 1.3-0)
Suggests: r-cran-gsl, r-cran-randomfields
Filename: pool/universe/r/r-cran-spatstat/r-cran-spatstat_1.37-0-1ubuntu1_amd64.deb
Size: 11103708
MD5sum: 63cf186f93f9de1e890d202717669cee
SHA1: a62f9bc9570e848a1e136452602c986dcc8057ef
SHA256: 0b0a2d61e0c4d65794335cddb260701c7fb02184169bb661e5364ad44eece95a
Description-en: 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: 9bbe4b77892099cfdf94da493ce584db
Homepage: http://cran.r-project.org/web/packages/spatstat/
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Origin: Ubuntu