binspp: Bayesian Inference for Neyman-Scott Point Processes

The Bayesian MCMC estimation of parameters for Thomas-type cluster point process with various inhomogeneities. It allows for inhomogeneity in (i) distribution of parent points, (ii) mean number of points in a cluster, (iii) cluster spread. The package also allows for the Bayesian MCMC algorithm for the homogeneous generalized Thomas process. The cluster size is allowed to have a variance that is greater or less than the expected value (cluster sizes are over or under dispersed). Details are described in Dvořák, Remeš, Beránek & Mrkvička (2022) <arXiv: 10.48550/arXiv.2205.07946>.

Version:	0.1.26
Depends:	R (≥ 3.5.0)
Imports:	Rcpp, VGAM, cluster, mvtnorm, spatstat, spatstat.model, spatstat.geom, spatstat.random
LinkingTo:	Rcpp, RcppArmadillo, RcppEigen
Published:	2022-12-08
DOI:	10.32614/CRAN.package.binspp
Author:	Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre]
Maintainer:	Remes Radim <inrem at jcu.cz>
License:	GPL-3
URL:	https://github.com/tomasmrkvicka/binspp
NeedsCompilation:	yes
CRAN checks:	binspp results

Documentation:

Reference manual:

binspp.pdf

Downloads:

Package source:	binspp_0.1.26.tar.gz
Windows binaries:	r-devel: binspp_0.1.26.zip, r-release: binspp_0.1.26.zip, r-oldrel: binspp_0.1.26.zip
macOS binaries:	r-release (arm64): binspp_0.1.26.tgz, r-oldrel (arm64): binspp_0.1.26.tgz, r-release (x86_64): binspp_0.1.26.tgz, r-oldrel (x86_64): binspp_0.1.26.tgz
Old sources:	binspp archive

Linking:

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