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gwrf
View on CRAN: Click
here
Download and install gwrf package within the R console
Install from CRAN:
install.packages("gwrf")
Install from Github:
library("remotes")
install_github("cran/gwrf") Install by package version:
library("remotes")
install_version("gwrf", "0.1.1") Attach the package and use:
library("gwrf")
Maintained by
Erich Seamon
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First Published: 2026-08-24
Latest Update: 2026-08-24
Description:
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>.
How to cite:
Erich Seamon (2026). gwrf: Geographically Weighted Random Forests. R package version 0.1.1, https://cran.r-project.org/web/packages/gwrf. Accessed 10 Nov. 2026.
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