Package: gwzinbr 0.1.0
gwzinbr: Geographically Weighted Zero Inflated Negative Binomial Regression
Fits a geographically weighted regression model using zero inflated probability distributions. Has the zero inflated negative binomial distribution (zinb) as default, but also accepts the zero inflated Poisson (zip), negative binomial (negbin) and Poisson distributions. Can also fit the global versions of each regression model. Da Silva, A. R. & De Sousa, M. D. R. (2023). "Geographically weighted zero-inflated negative binomial regression: A general case for count data", Spatial Statistics <doi:10.1016/j.spasta.2023.100790>. Brunsdon, C., Fotheringham, A. S., & Charlton, M. E. (1996). "Geographically weighted regression: a method for exploring spatial nonstationarity", Geographical Analysis, <doi:10.1111/j.1538-4632.1996.tb00936.x>. Yau, K. K. W., Wang, K., & Lee, A. H. (2003). "Zero-inflated negative binomial mixed regression modeling of over-dispersed count data with extra zeros", Biometrical Journal, <doi:10.1002/bimj.200390024>.
Authors:
gwzinbr_0.1.0.tar.gz
gwzinbr_0.1.0.zip(r-4.7-any)gwzinbr_0.1.0.zip(r-4.6-any)gwzinbr_0.1.0.zip(r-4.5-any)
gwzinbr_0.1.0.tgz(r-4.6-any)gwzinbr_0.1.0.tgz(r-4.5-any)
gwzinbr_0.1.0.tar.gz(r-4.7-any)gwzinbr_0.1.0.tar.gz(r-4.6-any)
gwzinbr_0.1.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
gwzinbr/json (API)
| # Install 'gwzinbr' in R: |
| install.packages('gwzinbr', repos = c('https://jessicavasconcelos.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jessicavasconcelos/gwzinbr/issues
- southkorea_covid19 - South Korea COVID-19 dataset
Last updated from:e7b6bb2e34. Checks:7 ERROR, 2 OK. Indexed: yes.
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Golden Section Search | Golden |
| Geographically Weighted Zero Inflated Negative Binomial Regression | gwzinbr |
| Hello, World! | hello |
| South Korea COVID-19 dataset | southkorea_covid19 |
