gwrf: Geographically Weighted Random Forests

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>.

Package details

AuthorErich Seamon [aut, cre, cph]
MaintainerErich Seamon <erich_seamon@baylor.edu>
LicenseMIT + file LICENSE
Version0.1.1
URL https://github.com/hac-lab/gwrf
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("gwrf")

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gwrf documentation built on Aug. 24, 2026, 5:15 p.m.