Bayesian inference for Neyman-Scott point processes (R package)
These instructions will get you a copy of the project up and running on your local machine for development and testing purposes. See deployment for notes on how to deploy the project on a live system.
R software with VGAM, spatstat, FNN and cluster libraries installed. Additional required packages are: Rcpp, RcppArmadillo and RcppEigen.
In R shell write:
> install.packages(c("VGAM", "spatstat", "FNN", "cluster"))
> install.packages(c("Rcpp", "RcppArmadillo", "RcppEigen"))
Install package by downloading from CRAN:
install.packages("binspp")
You can also download binspp.tar.gz package and install it to your R software.
install.packages("C:/path/to/directory/binspp.tar.gz",
repos = NULL,
lib = "C:/path/to/libraryDirectory")
Load data dataset_N4.Rdata, run example scripts to test package functionality.
R Studio or any other R software.
- RStudio - The R Studio
We use GitHub for versioning. For the versions available, see the binspp. You can also get binspp package on the CRAN.
- Tomas Mrkvicka - creator, author - ResearchGate
- Jiri Dvorak - author - ResearchGate
- Ladislav Beranek - author - GitHub
- Radim Remes - author, maintainer - GitHub
See also the list of contributors who participated in this project.
This project is licensed under the GNU GPL 3 License - see the LICENSE file for details
Anderson, C. Mrkvička T. (2020). Inference for cluster point processes with over- or under-dispersed cluster sizes, Statistics and computing 30, 1573–1590. https://doi.org/10.1007/s11222-020-09960-8