Package: SpatialML
Type: Package
Title: Spatial Machine Learning
Version: 1.8.2
Date: 2026-07-06
Authors@R: c(
    person("Stamatis", "Kalogirou",
           email = "stamatis.science@gmail.com",
           role = c("aut", "cre", "cph"),
           comment = c(ORCID = "0000-0003-1949-6248")),
    person("Stefanos", "Georganos",
           email = "stefanos.georganos@kau.se",
           role = "aut"))
Description: Implements a spatial extension of the random forest
        algorithm (Georganos et al. (2019)
        <doi:10.1080/10106049.2019.1595177>). Provides a Geographically
        Weighted Random Forest regression and a routine to find the
        optimal bandwidth (Georganos and Kalogirou (2022)
        <doi:10.3390/ijgi11090471>). A lightweight cross-validation
        helper for tuning the 'mtry' parameter of a random forest and a
        generator of synthetic spatial test data are also included. The
        package depends on 'ranger' as its single random-forest
        back-end.
License: GPL (>= 2)
Encoding: UTF-8
Language: en-GB
LazyData: true
Depends: R (>= 4.1.0)
Imports: ranger (>= 0.15.1), stats, graphics, utils
Suggests: knitr, markdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
URL: https://stamatisgeoai.eu/
NeedsCompilation: no
Packaged: 2026-07-06 12:50:14 UTC; root
Author: Stamatis Kalogirou [aut, cre, cph] (ORCID:
        <https://orcid.org/0000-0003-1949-6248>), Stefanos Georganos
        [aut]
Maintainer: Stamatis Kalogirou <stamatis.science@gmail.com>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-07-06 11:08:41 UTC
RemoteUrl: https://github.com/cran/SpatialML
RemoteRef: HEAD
RemoteSha: c5991c81cde7b2a0a695a575e52135630494d4f7