binspp: Bayesian Inference for Neyman-Scott Point Processes (original) (raw)
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 |
| License: | GPL-3 |
| URL: | https://github.com/tomasmrkvicka/binspp |
| NeedsCompilation: | yes |
| CRAN checks: | binspp results |
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