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blockCV: Spatial and Environmental Blocking for Cross-Validation
Creates spatially or environmentally separated, or group-preserving, training and testing folds for k-fold, leave-group-out, and leave-one-out cross-validation. Provides spatial blocking, clustering, buffering, and nearest-neighbour distance-matching methods, together with tools to visualise folds, summarise fold sizes and class balance, and assess train–test separation and environmental novelty. Also estimates spatial autocorrelation ranges in point samples and continuous raster covariates to provide an initial distance scale for designing spatial folds. Methods are described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.
Package details |
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| Author | Roozbeh Valavi [aut, cre] (ORCID: <https://orcid.org/0000-0003-2495-5277>), Jane Elith [aut], José Lahoz-Monfort [aut], Ian Flint [aut], Gurutzeta Guillera-Arroita [aut] |
| Maintainer | Roozbeh Valavi <valavi.r@gmail.com> |
| License | GPL (>= 3) |
| Version | 4.0-0 |
| URL | https://github.com/rvalavi/blockCV |
| Package repository | View on CRAN |
| Installation |
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