geography/R-spatstat - The NetBSD Packages Collection

Spatial Point Pattern Analysis, Model-Fitting, Simulation, Tests

Comprehensive open-source toolbox for analysing Spatial Point
Patterns. Focused mainly on two-dimensional point patterns, including
multitype/marked points, in any spatial region. Also supports
three-dimensional point patterns, space-time point patterns in any
number of dimensions, point patterns on a linear network, and patterns
of other geometrical objects. Supports spatial covariate data such as
pixel images. Contains over 2000 functions for plotting spatial data,
exploratory data analysis, model-fitting, simulation, spatial
sampling, model diagnostics, and formal inference. Many data types and
exploratory methods are supported.  Formal hypothesis tests of random
pattern and tests for covariate effects are also supported. Parametric
models can be fitted to point pattern data using the functions ppm(),
kppm(), slrm(), dppm() similar to glm(). Types of models include
Poisson, Gibbs and Cox point processes, Neyman-Scott cluster
processes, and determinantal point processes. Models may involve
dependence on covariates, inter-point interaction, cluster formation
and dependence on marks. Models are fitted by maximum likelihood,
logistic regression, minimum contrast, and composite likelihood
methods. A model can be fitted to a list of point patterns (replicated
point pattern data) using the function mppm(). The model can include
random effects and fixed effects depending on the experimental design,
in addition to all the features listed above.  Fitted point process
models can be simulated, automatically. Formal hypothesis tests of a
fitted model are supported along with basic tools for model selection.

Build dependencies

pkgtools/mktools pkgtools/cwrappers

Runtime dependencies

geography/R-deldir geography/R-spatstat.data geography/R-spatstat.geom geography/R-spatstat.linnet geography/R-spatstat.model geography/R-spatstat.utils math/R-abind math/R-goftest graphics/R-polyclip math/R-tensor math/R math/R

Binary packages

OSArchitectureVersion
NetBSD 10.0aarch64R-spatstat-3.0.7.tgz
NetBSD 10.0aarch64R-spatstat-3.0.7.tgz
NetBSD 10.0aarch64ebR-spatstat-3.0.7.tgz
NetBSD 10.0aarch64ebR-spatstat-3.0.7.tgz
NetBSD 10.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 10.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 10.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 10.0i386R-spatstat-3.0.7.tgz
NetBSD 10.0i386R-spatstat-3.0.7.tgz
NetBSD 10.0powerpcR-spatstat-2.2.0.tgz
NetBSD 10.0powerpcR-spatstat-2.2.0.tgz
NetBSD 10.0powerpcR-spatstat-3.0.7.tgz
NetBSD 10.0x86_64R-spatstat-3.0.7.tgz
NetBSD 10.0x86_64R-spatstat-3.0.7.tgz
NetBSD 9.0aarch64R-spatstat-3.0.7.tgz
NetBSD 9.0aarch64R-spatstat-3.0.7.tgz
NetBSD 9.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 9.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 9.0earmv7hfR-spatstat-3.0.7.tgz
NetBSD 9.0i386R-spatstat-3.0.7.tgz
NetBSD 9.0i386R-spatstat-3.0.7.tgz
NetBSD 9.0powerpcR-spatstat-2.2.0.tgz
NetBSD 9.0powerpcR-spatstat-2.2.0.tgz
NetBSD 9.0powerpcR-spatstat-3.0.7.tgz
NetBSD 9.0x86_64R-spatstat-3.0.7.tgz
NetBSD 9.0x86_64R-spatstat-3.0.7.tgz
NetBSD 9.3x86_64R-spatstat-3.0.7.tgz

Binary packages can be installed with the high-level tool pkgin (which can be installed with pkg_add) or pkg_add(1) (installed by default). The NetBSD packages collection is also designed to permit easy installation from source.

Available build options

(none)

Known vulnerabilities

The pkg_admin audit command locates any installed package which has been mentioned in security advisories as having vulnerabilities.

Please note the vulnerabilities database might not be fully accurate, and not every bug is exploitable with every configuration.


Problem reports, updates or suggestions for this package should be reported with send-pr.