GWlasso: Geographically Weighted Lasso
Performs geographically weighted Lasso regressions. Find optimal bandwidth, fit a geographically weighted lasso or ridge regression, and make predictions. These methods are specially well suited for ecological inferences. Bandwidth selection algorithm is from A. Comber and P. Harris (2018) <doi:10.1007/s10109-018-0280-7>.
| Version: | 1.0.2 |
| Depends: | R (≥ 3.5.0) |
| Imports: | dplyr,ggplot2,ggside,glmnet,GWmodel,lifecycle,magrittr, methods,progress,rlang,sf,tidyr |
| Suggests: | knitr,maps,rmarkdown |
| Published: | 2025-09-26 |
| DOI: | 10.32614/CRAN.package.GWlasso |
| Author: | Matthieu Mulot [aut, cre, cph], Sophie Erb [aut] |
| Maintainer: | Matthieu Mulot <matthieu.mulot at gmail.com> |
| BugReports: | https://github.com/nibortolum/GWlasso/issues |
| License: | MIT + fileLICENSE |
| URL: | https://github.com/nibortolum/GWlasso,https://nibortolum.github.io/GWlasso/ |
| NeedsCompilation: | no |
| Citation: | GWlasso citation info |
| Materials: | README,NEWS |
| CRAN checks: | GWlasso results |
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