How to Install and Uninstall r-cran-spatstat Package on Ubuntu 21.10 (Impish Indri)

Last updated: May 10,2024

1. Install "r-cran-spatstat" package

Please follow the guidance below to install r-cran-spatstat on Ubuntu 21.10 (Impish Indri)

$ sudo apt update $ sudo apt install r-cran-spatstat

2. Uninstall "r-cran-spatstat" package

This tutorial shows how to uninstall r-cran-spatstat on Ubuntu 21.10 (Impish Indri):

$ sudo apt remove r-cran-spatstat $ sudo apt autoclean && sudo apt autoremove

3. Information about the r-cran-spatstat package on Ubuntu 21.10 (Impish Indri)

Package: r-cran-spatstat
Architecture: amd64
Version: 1.64-1-1build1
Priority: optional
Section: universe/gnu-r
Origin: Ubuntu
Maintainer: Ubuntu Developers
Original-Maintainer: Debian R Packages Maintainers
Bugs: https://bugs.launchpad.net/ubuntu/+filebug
Installed-Size: 18765
Depends: r-base-core (>= 4.0.0.20200528-1), r-api-4.0, r-cran-spatstat.data (>= 1.4-2), r-cran-nlme, r-cran-rpart, r-cran-spatstat.utils (>= 1.17-0), r-cran-mgcv, r-cran-matrix, r-cran-deldir (>= 0.0-21), r-cran-abind, r-cran-tensor, r-cran-polyclip (>= 1.10-0), r-cran-goftest (>= 1.2-2), libc6 (>= 2.29), libstdc++6 (>= 4.1.1)
Recommends: r-cran-gsl, r-cran-randomfields
Suggests: r-cran-sm, r-cran-maptools (>= 0.9-9), r-cran-locfit, r-cran-spatial, r-cran-randomfieldsutils (>= 0.3.3.1)
Filename: pool/universe/r/r-cran-spatstat/r-cran-spatstat_1.64-1-1build1_amd64.deb
Size: 16253080
MD5sum: 7f38b7cf5c4a09e73ff285d280caddad
SHA1: 64a5b14e4127414026006a681f8dd3569590be7c
SHA256: 15bd69d4d708761bb017ac92774bea1e992c30f5cdd990ab1b0c8e5ef9c0144a
SHA512: 91f0820a42aecc90b208cbfc75c9fd0c6e35f9e766b925913e21a9e44f535ce1b7be3d6bf4fe7b3447720a97e9c4c4ffa35e6949ba44201f768c10922eb5d121
Homepage: https://cran.r-project.org/package=spatstat
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