doi:10.18637/jss.v111.i07>.">

mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3' (original) (raw)

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>.

Version: 2.3.4
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
Published: 2025-09-12
DOI: 10.32614/CRAN.package.mlr3spatiotempcv
Author: Patrick Schratz ORCID iD [aut, cre], Marc Becker ORCID iD [aut], Jannes Muenchow ORCID iD [ctb], Michel Lang ORCID iD [ctb]
Maintainer: Patrick Schratz <patrick.schratz at gmail.com>
BugReports: https://github.com/mlr-org/mlr3spatiotempcv/issues
License: LGPL-3
URL: https://mlr3spatiotempcv.mlr-org.com/,https://github.com/mlr-org/mlr3spatiotempcv,https://mlr3book.mlr-org.com
NeedsCompilation: no
Citation: mlr3spatiotempcv citation info
Materials: README, NEWS
In views: Spatial, SpatioTemporal
CRAN checks: mlr3spatiotempcv results

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