binspp
Bayesian inference for Neyman-Scott point processes (R package)
Science Score: 36.0%
This score indicates how likely this project is to be science-related based on various indicators:
-
○CITATION.cff file
-
✓codemeta.json file
Found codemeta.json file -
○.zenodo.json file
-
✓DOI references
Found 2 DOI reference(s) in README -
✓Academic publication links
Links to: researchgate.net -
○Academic email domains
-
○Institutional organization owner
-
○JOSS paper metadata
-
○Scientific vocabulary similarity
Low similarity (11.3%) to scientific vocabulary
Repository
Bayesian inference for Neyman-Scott point processes (R package)
Basic Info
- Host: GitHub
- Owner: tomasmrkvicka
- Language: R
- Default Branch: master
- Size: 32.3 MB
Statistics
- Stars: 1
- Watchers: 0
- Forks: 1
- Open Issues: 0
- Releases: 1
Metadata Files
README.md
binspp v0.2.2
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, cluster and fields libraries installed. Additional required packages are: Rcpp, RcppArmadillo and RcppEigen.
``` In R shell write:
install.packages(c("VGAM", "spatstat", "FNN", "cluster", "fields")) 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.
- RStudio - The R Studio
Versioning
We use GitHub for versioning. For the versions available, see the binspp. You can also get binspp package on the CRAN.
Authors
- Tomas Mrkvicka - creator, author - ResearchGate
- Jiri Dvorak - author - ResearchGate
- Ladislav Beranek - author - GitHub
- Radim Remes - author, maintainer - GitHub
- Jaewoo Park - contributor - GitHub
- Sujeong Lee - contributor - GitHub
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
Owner
- Name: tomasmrkvicka
- Login: tomasmrkvicka
- Kind: organization
- Repositories: 1
- Profile: https://github.com/tomasmrkvicka
GitHub Events
Total
- Push event: 20
Last Year
- Push event: 20
Packages
- Total packages: 1
-
Total downloads:
- cran 625 last-month
- Total dependent packages: 0
- Total dependent repositories: 0
- Total versions: 6
- Total maintainers: 1
cran.r-project.org: binspp
Bayesian Inference for Neyman-Scott Point Processes
- Homepage: https://github.com/tomasmrkvicka/binspp
- Documentation: http://cran.r-project.org/web/packages/binspp/binspp.pdf
- License: GPL-3
-
Latest release: 0.2.2
published about 1 year ago
Rankings
Maintainers (1)
Dependencies
- R >= 3.5.0 depends
- Rcpp * imports
- VGAM * imports
- cluster * imports
- mvtnorm * imports
- spatstat * imports
- spatstat.geom * imports
- spatstat.model * imports
- spatstat.random * imports