Source: r-cran-spatstat Maintainer: Debian R Packages Maintainers Uploaders: Andreas Tille Section: gnu-r Testsuite: autopkgtest-pkg-r Priority: optional Build-Depends: debhelper-compat (= 13), dh-r, r-base-dev, r-cran-spatstat.data (>= 3.0-4), r-cran-spatstat.geom (>= 3.2-9), r-cran-spatstat.random (>= 3.2-3), r-cran-spatstat.explore (>= 3.2-7), r-cran-spatstat.model, r-cran-spatstat.linnet (>= 3.1-5), r-cran-spatstat.utils (>= 3.0-4) Standards-Version: 4.7.0 Vcs-Browser: https://salsa.debian.org/r-pkg-team/r-cran-spatstat Vcs-Git: https://salsa.debian.org/r-pkg-team/r-cran-spatstat.git Homepage: https://cran.r-project.org/package=spatstat Rules-Requires-Root: no Package: r-cran-spatstat Architecture: any Depends: ${R:Depends}, ${shlibs:Depends}, ${misc:Depends} Recommends: ${R:Recommends} Suggests: ${R:Suggests} 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).