Package: mlr3spatiotempcv
Title: Spatiotemporal Resampling Methods for 'mlr3'
Version: 2.3.4
Authors@R: c(
    person("Patrick", "Schratz", , "patrick.schratz@gmail.com", role = c("aut", "cre"),
           comment = c(ORCID = "0000-0003-0748-6624")),
    person("Marc", "Becker", , "marcbecker@posteo.de", role = "aut",
           comment = c(ORCID = "0000-0002-8115-0400")),
    person("Jannes", "Muenchow", , "jannes.muenchow@uni-jena.de", role = "ctb",
           comment = c(ORCID = "0000-0001-7834-4717")),
    person("Michel", "Lang", , "michellang@gmail.com", role = "ctb",
           comment = c(ORCID = "0000-0001-9754-0393"))
  )
Description: 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>.
License: LGPL-3
URL: https://mlr3spatiotempcv.mlr-org.com/,
        https://github.com/mlr-org/mlr3spatiotempcv,
        https://mlr3book.mlr-org.com
BugReports: https://github.com/mlr-org/mlr3spatiotempcv/issues
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
VignetteBuilder: knitr
Config/testthat/edition: 3
Config/testthat/parallel: true
Encoding: UTF-8
LazyData: true
NeedsCompilation: no
RoxygenNote: 7.3.3
Collate: 'aaa.R' 'ResamplingRepeatedSpCVBlock.R'
        'ResamplingRepeatedSpCVCoords.R' 'ResamplingRepeatedSpCVDisc.R'
        'ResamplingRepeatedSpCVEnv.R' 'ResamplingRepeatedSpCVTiles.R'
        'ResamplingRepeatedSpCVknndm.R' 'ResamplingRepeatedSptCVCstf.R'
        'ResamplingSpCVBlock.R' 'ResamplingSpCVBuffer.R'
        'ResamplingSpCVCoords.R' 'ResamplingSpCVDisc.R'
        'ResamplingSpCVEnv.R' 'ResamplingSpCVKnndm.R'
        'ResamplingSpCVTiles.R' 'ResamplingSptCVCstf.R'
        'TaskClassifST.R' 'TaskRegrST.R' 'Task_classif_diplodia.R'
        'Task_classif_ecuador.R' 'Task_regr_cookfarm_profiles.R'
        'as_task_classif_st.R' 'as_task_regr_st.R' 'autoplot.R'
        'autoplot_all_folds_dt.R' 'autoplot_all_folds_list.R'
        'autoplot_multi_fold_dt.R' 'autoplot_multi_fold_list.R'
        'autoplot_spcv_cstf.R' 'bibentries.R' 'helper.R'
        'helper_DataBackend.R' 'helper_autoplot.R' 'reexports.R'
        'zzz.R'
Packaged: 2025-09-12 10:00:14 UTC; pjs
Author: 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>)
Maintainer: Patrick Schratz <patrick.schratz@gmail.com>
Repository: CRAN
Date/Publication: 2025-09-12 10:40:02 UTC
Built: R 4.6.0; ; 2025-12-02 04:30:48 UTC; windows
