Spatial cross-validation and model evaluation for geospatial machine learning applications. Addresses spatial dependence in observations by implementing spatial block, buffered, and clustering cross-validation methods. Includes spatial leakage detection, model performance metrics, and spatial residual diagnostics for assessing model generalization across geographic space. Methods based on Brenning (2012) <doi:10.1016/j.cageo.2012.02.001>, Pohjankukka et al. (2017) <doi:10.1016/j.isprsjprs.2017.07.001>, and Roberts et al. (2017) <doi:10.1111/ecog.02881>.
| Version: | 0.1.0 |
| Depends: | R (≥ 3.5.0) |
| Imports: | sf (≥ 1.0-0) |
| Suggests: | dplyr (≥ 1.0.0), ggplot2 (≥ 3.4.0), tidymodels (≥ 1.0.0), rsample (≥ 1.0.0), testthat (≥ 3.0.0), knitr (≥ 1.40), rmarkdown (≥ 2.14), terra (≥ 1.5.0) |
| Published: | 2026-10-07 |
| DOI: | 10.32614/CRAN.package.spatialcvR (may not be active yet) |
| Author: | Mamadou SOW [aut, cre] |
| Maintainer: | Mamadou SOW <sowsalim01 at gmail.com> |
| BugReports: | https://github.com/sowsalim01/spatialcvR/issues |
| License: | MIT + file LICENSE |
| URL: | https://sowsalim01.github.io/spatialcvR/, https://github.com/sowsalim01/spatialcvR |
| NeedsCompilation: | no |
| Materials: | NEWS |
| CRAN checks: | spatialcvR results |
| Reference manual: | spatialcvR.html , spatialcvR.pdf |
| Vignettes: |
Introduction to Spatial Cross-Validation (source, R code) Model Evaluation and Comparison (source, R code) Spatial Cross-Validation Methods (source, R code) Spatial Leakage Detection (source, R code) |
| Package source: | spatialcvR_0.1.0.tar.gz |
| Windows binaries: | r-devel: not available, r-release: not available, r-oldrel: not available |
| macOS binaries: | r-release (arm64): not available, r-oldrel (arm64): not available, r-release (x86_64): not available, r-oldrel (x86_64): not available |
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