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binspp  

Bayesian Inference for Neyman-Scott Point Processes
View on CRAN: Click here


Download and install binspp package within the R console
Install from CRAN:
install.packages("binspp")

Install from Github:
library("remotes")
install_github("cran/binspp")

Install by package version:
library("remotes")
install_version("binspp", "0.2.4")



Attach the package and use:
library("binspp")
Maintained by
Remes Radim
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-05-27
Latest Update: 2025-05-05
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 Dvor
How to cite:
Remes Radim (2022). binspp: Bayesian Inference for Neyman-Scott Point Processes. R package version 0.2.4, https://cran.r-project.org/web/packages/binspp. Accessed 30 Oct. 2026.
Previous versions and publish date:
(2026-07-09 07:22), 0.1.18 (2022-05-27 09:40), 0.1.20 (2022-06-07 22:30), 0.1.24 (2022-10-08 08:10), 0.1.26 (2022-12-08 19:30), 0.2.0 (2025-04-24 14:30), 0.2.2 (2025-05-05 20:30), 0.2.3 (2025-12-04 00:40)
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Complete documentation for binspp
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