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r-cran-spatstat package

r-cran-spatstat 2.2-0-1 source package in Ubuntu

Changelog

r-cran-spatstat (2.2-0-1) unstable; urgency=medium

  * New upstream version
  * Standards-Version: 4.5.1 (routine-update)
  * debhelper-compat 13 (routine-update)
  * Upstream has moved test suite to other packages thus removing
    autopkgtest

 -- Andreas Tille <email address hidden>  Wed, 15 Sep 2021 14:01:49 +0200

Upload details

Uploaded by:
Debian R Packages Maintainers
Uploaded to:
Sid
Original maintainer:
Debian R Packages Maintainers
Architectures:
any
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

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Downloads

File Size SHA-256 Checksum
r-cran-spatstat_2.2-0-1.dsc 2.2 KiB 1cd0a5c15e5f33a816ae45895c30883d787b9552c36e2437a1fb27c0ebe397e9
r-cran-spatstat_2.2-0.orig.tar.gz 3.4 MiB 8f0f90e8d5af1e2e97ef5f01e595511916290d554fc1ae3ad7b217605bd4e353
r-cran-spatstat_2.2-0-1.debian.tar.xz 4.3 KiB b75d089f1b7508aca5a7216dd29292b6f872100986f02323a21c129dcfb5b59b

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Binary packages built by this source

r-cran-spatstat: 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).