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Implements a spatial extension of the random forest algorithm (Georganos et al. (2019) <doi:10.1080/10106049.2019.1595177>). Allows for a geographically weighted random forest regression including a function to find the optical bandwidth. (Georganos and Kalogirou (2022) <https://www.mdpi.com/2220-9964/11/9/471>).
| Version: | 0.1.7 |
| Depends: | R (≥ 4.3.0), ranger (≥ 0.15.1), caret (≥ 6.0), randomForest (≥ 4.7) |
| Published: | 2024-04-02 |
| DOI: | 10.32614/CRAN.package.SpatialML |
| Author: | Stamatis Kalogirou [aut, cre], Stefanos Georganos [aut, ctb] |
| Maintainer: | Stamatis Kalogirou <stamatis.science at gmail.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: | https://stamatisgeoai.eu/ |
| NeedsCompilation: | no |
| CRAN checks: | SpatialML results |
| Reference manual: | SpatialML.pdf |
| Package source: | SpatialML_0.1.7.tar.gz |
| Windows binaries: | r-devel: SpatialML_0.1.7.zip, r-release: SpatialML_0.1.7.zip, r-oldrel: SpatialML_0.1.7.zip |
| macOS binaries: | r-release (arm64): SpatialML_0.1.7.tgz, r-oldrel (arm64): SpatialML_0.1.7.tgz, r-release (x86_64): SpatialML_0.1.7.tgz, r-oldrel (x86_64): SpatialML_0.1.7.tgz |
| Old sources: | SpatialML archive |
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These binaries (installable software) and packages are in development.
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