Geographically Weighted Random Forests R package gwrf version 0.1.1 Fits geographically weighted random forest models using spatially localized training neighborhoods and 'ranger' as the random forest engine. Supports fixed-distance and adaptive neighborhoods defined by observation rows or unique spatial locations, including repeated observations at the same location. Provides local predictions and permutation-based variable importance for examining spatial variation in predictive relationships. The geographical random forest approach is described by Georganos et al. (2021) <doi:10.1080/10106049.2019.1595177>, and the 'ranger' engine by Wright and Ziegler (2017) <doi:10.18637/jss.v077.i01>. Software Imports: ranger, tibble, dplyr, pbapply, stats Suggests: testthat (>= 3.0.0) Erich Seamon <erich_seamon@baylor.edu> Comprehensive R Archive Network (CRAN) Erich Seamon [aut, cre, cph] MIT + file LICENSE (https://CRAN.R-project.org/package=gwrf/LICENSE) 2026-08-24 application/tgz https://CRAN.R-project.org/package=gwrf doi:10.32614/CRAN.package.gwrf