Spatiotemporal Resampling Methods for 'mlr3' R package mlr3spatiotempcv version 2.3.5 CRAN Task View: Spatial (https://CRAN.R-project.org/view=Spatial) CRAN Task View: SpatioTemporal (https://CRAN.R-project.org/view=SpatioTemporal) Extends the mlr3 machine learning framework with spatio-temporal resampling methods to account for the presence of spatiotemporal autocorrelation (STAC) in predictor variables. STAC may cause highly biased performance estimates in cross-validation if ignored. A JSS article is available at <doi:10.18637/jss.v111.i07>. Software Depends: mlr3 (>= 0.12.0), R (>= 3.5.0) Imports: checkmate, data.table, ggplot2 (>= 3.4.0), mlr3misc (>= 0.11.0), paradox, R6, utils Suggests: bbotk, blockCV (>= 3.1.2), caret, CAST (>= 0.8.0), ggsci, ggtext, here, knitr, lgr, mlr3filters (>= 0.7.0.9000), mlr3pipelines, mlr3spatial, mlr3tuning, patchwork, plotly, rmarkdown, rpart, sf, sperrorest, terra, testthat (>= 3.0.0), twosamples, vdiffr (>= 1.0.0), withr Patrick Schratz <patrick.schratz@gmail.com> Comprehensive R Archive Network (CRAN) Patrick Schratz [aut, cre] (ORCID: <https://orcid.org/0000-0003-0748-6624>), Marc Becker [aut] (ORCID: <https://orcid.org/0000-0002-8115-0400>), Jannes Muenchow [ctb] (ORCID: <https://orcid.org/0000-0001-7834-4717>), Michel Lang [ctb] (ORCID: <https://orcid.org/0000-0001-9754-0393>) LGPL-3 2026-08-03 application/tgz https://CRAN.R-project.org/package=mlr3spatiotempcv doi:10.32614/CRAN.package.mlr3spatiotempcv