mlr3spatiotempcv: Spatiotemporal Resampling Methods for 'mlr3'

Extends the mlr3 ML 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.

Version: 0.1.0
Depends: R (≥ 3.5.0)
Imports: checkmate, data.table, ggplot2, mlr3 (≥ 0.7.0), mlr3misc (≥ 0.1.7), paradox, R6, testthat (≥ 3.0.0), utils
Suggests: bbotk, blockCV (≥ 2.1.1), CAST, ggsci, ggtext, GSIF, knitr, lgr, mlr3filters, mlr3pipelines, mlr3tuning, patchwork, plotly, rmarkdown, rpart, sf, skmeans, vdiffr, withr
Published: 2020-11-11
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>
License: LGPL-3
NeedsCompilation: no
Materials: README NEWS
CRAN checks: mlr3spatiotempcv results


Reference manual: mlr3spatiotempcv.pdf
Vignettes: Getting Started
Spatiotemporal Visualization
Package source: mlr3spatiotempcv_0.1.0.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release: mlr3spatiotempcv_0.1.0.tgz, r-oldrel: mlr3spatiotempcv_0.1.0.tgz


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