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: 0.1.20
Depends: R (≥ 3.5.0)
Imports: Rcpp, VGAM, cluster, mvtnorm, spatstat, spatstat.core, spatstat.geom, spatstat.random
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
Published: 2022-06-07
Author: Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre]
Maintainer: Remes Radim <inrem at>
License: GPL-3
NeedsCompilation: yes
CRAN checks: binspp results


Reference manual: binspp.pdf


Package source: binspp_0.1.20.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): binspp_0.1.20.tgz, r-oldrel (arm64): binspp_0.1.20.tgz, r-release (x86_64): binspp_0.1.20.tgz, r-oldrel (x86_64): binspp_0.1.20.tgz
Old sources: binspp archive


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