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: 1.0.1 Depends: R (≥ 3.5.0) Imports: dplyr, ggplot2, ggside, glmnet, GWmodel, lifecycle, magrittr, methods, progress, rlang, sf, tidyr Suggests: knitr, maps, rmarkdown Published: 2024-11-22 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 + file LICENSE URL: https://github.com/nibortolum/GWlasso, https://nibortolum.github.io/GWlasso/ NeedsCompilation: no Materials: README NEWS CRAN checks: GWlasso results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=GWlasso to link to this page.
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