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>.
Version: |
0.1.0 |
Depends: |
R (≥ 3.5.0) |
Imports: |
sp |
Published: |
2024-06-10 |
DOI: |
10.32614/CRAN.package.gwzinbr |
Author: |
Jéssica Vasconcelos [aut, cre],
Juliana Rosa [aut],
Alan da Silva [aut] |
Maintainer: |
Jéssica Vasconcelos <jehh.vasconcelosabreu at gmail.com> |
License: |
GPL-3 |
NeedsCompilation: |
no |
Materials: |
NEWS |
CRAN checks: |
gwzinbr results |
Documentation:
Downloads:
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