Bayesian Inference for Neyman-Scott Point Processes R package binspp version 0.2.4 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>. Software 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) Remes Radim <inrem@jcu.cz> Comprehensive R Archive Network (CRAN) Mrkvicka Tomas [aut], Dvorak Jiri [aut], Beranek Ladislav [aut], Remes Radim [aut, cre], Park Jaewoo [ctb], Lee Sujeong [ctb] GPL-3 2026-06-16 application/tgz https://CRAN.R-project.org/package=binspp doi:10.32614/CRAN.package.binspp