Package: binspp
Type: Package
Title: Bayesian Inference for Neyman-Scott Point Processes
Version: 0.2.2
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) <arXiv: 10.48550/arXiv.2205.07946>.
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
LinkingTo: Rcpp, RcppArmadillo, RcppEigen
RoxygenNote: 7.3.2
NeedsCompilation: yes
Packaged: 2025-05-05 09:50:49 UTC; inrem
Author: Mrkvicka Tomas [aut],
  Dvorak Jiri [aut],
  Beranek Ladislav [aut],
  Remes Radim [aut, cre],
  Park Jaewoo [ctb],
  Lee Sujeong [ctb]
Maintainer: Remes Radim <inrem@jcu.cz>
Repository: CRAN
Date/Publication: 2025-05-05 18:30:07 UTC
Built: R 4.3.3; aarch64-apple-darwin20; 2025-05-05 19:08:43 UTC; unix
Archs: binspp.so.dSYM
