GitHub - tomasmrkvicka/binspp: Bayesian inference for Neyman-Scott point processes (R package) (original) (raw)

binspp v0.1.26

Bayesian inference for Neyman-Scott point processes (R package)

Getting Started

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.

Prerequisites

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"))

Installing

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")

Running the tests

Load data dataset_N4.Rdata, run example scripts to test package functionality.

Built With

R Studio or any other R software.

Versioning

We use GitHub for versioning. For the versions available, see the binspp. You can also get binspp package on the CRAN.

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the GNU GPL 3 License - see the LICENSE file for details

Acknowledgments

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