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gwzinbr  

Geographically Weighted Zero Inflated Negative Binomial Regression
View on CRAN: Click here


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

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

Install by package version:
library("remotes")
install_version("gwzinbr", "0.1.0")



Attach the package and use:
library("gwzinbr")
Maintained by
Jéssica Vasconcelos
[Scholar Profile | Author Map]
First Published: 2024-06-10
Latest Update: 2024-06-10
Description:
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>.
How to cite:
Jéssica Vasconcelos (2024). gwzinbr: Geographically Weighted Zero Inflated Negative Binomial Regression. R package version 0.1.0, https://cran.r-project.org/web/packages/gwzinbr. Accessed 17 Feb. 2025.
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