Package: binspp Type: Package Title: Bayesian Inference for Neyman-Scott Point Processes Version: 0.2.4 Authors@R: c( person("Mrkvicka", "Tomas", email = "mrkvicka.toma@gmail.com", role = "aut"), person("Dvorak","Jiri", email = "dvorak@karlin.mff.cuni.cz", role = "aut"), person("Beranek", "Ladislav", email = "beranek@jcu.cz", role = c("aut")), person("Remes","Radim", email = "inrem@jcu.cz", role = c("aut", "cre")), person("Park", "Jaewoo", email = "jwpark88@yonsei.ac.kr", role = "ctb"), person("Lee","Sujeong", email = "dltnwjd2304@gmail.com", role = "ctb") ) Description: 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) . License: GPL-3 URL: https://github.com/tomasmrkvicka/binspp Encoding: UTF-8 LazyData: true Depends: R (>= 3.5.0) Imports: Rcpp, VGAM, cluster, mvtnorm, spatstat, spatstat.model, spatstat.geom, spatstat.random, fields, stats LinkingTo: Rcpp, RcppArmadillo, RcppEigen Suggests: knitr, rmarkdown, testthat (>= 3.0.0) Config/testthat/edition: 3 RoxygenNote: 7.3.3 NeedsCompilation: yes Packaged: 2026-06-16 21:16:07 UTC; root Author: Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre], Park Jaewoo [ctb], Lee Sujeong [ctb] Maintainer: Remes Radim VignetteBuilder: knitr Repository: https://tomasmrkvicka.r-universe.dev Date/Publication: 2026-06-16 19:52:18 UTC RemoteUrl: https://github.com/tomasmrkvicka/binspp RemoteRef: HEAD RemoteSha: 560bc3bdbe99c8f999f5f020af404a5dab1de89d