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.


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Reference manual

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install.packages("mlr3spatiotempcv")

0.1.1 by Patrick Schratz, 2 months ago


https://mlr3spatiotempcv.mlr-org.com/, https://github.com/mlr-org/mlr3spatiotempcv, https://mlr3book.mlr-org.com


Report a bug at https://github.com/mlr-org/mlr3spatiotempcv/issues


Browse source code at https://github.com/cran/mlr3spatiotempcv


Authors: Patrick Schratz [aut, cre] , Marc Becker [aut] , Jannes Muenchow [ctb] , Michel Lang [ctb]


Documentation:   PDF Manual  


LGPL-3 license


Imports checkmate, data.table, ggplot2, mlr3, mlr3misc, paradox, R6, testthat, utils

Suggests bbotk, blockCV, CAST, ggsci, ggtext, GSIF, knitr, lgr, mlr3filters, mlr3pipelines, mlr3tuning, patchwork, plotly, rmarkdown, rpart, sf, skmeans, vdiffr, withr


See at CRAN