spatialcvR: Spatial Cross-Validation for Machine Learning

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
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

Documentation:

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)

Downloads:

Package source:	spatialcvR_0.1.0.tar.gz
Windows binaries:	r-devel: not available, r-release: not available, r-oldrel: spatialcvR_0.1.0.zip
macOS binaries:	r-release (arm64): spatialcvR_0.1.0.tgz, r-oldrel (arm64): spatialcvR_0.1.0.tgz, r-release (x86_64): spatialcvR_0.1.0.tgz, r-oldrel (x86_64): spatialcvR_0.1.0.tgz

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