mlr3spatiotempcv
Package website: release | dev
Spatiotemporal resampling methods for mlr3.
This package extends the mlr3 package framework with spatiotemporal resampling and visualization methods.
If you prefer the tidymodels ecosystem, have a look at the {spatialsample} package for spatial sampling methods.
Installation
CRAN version
install.packages("mlr3spatiotempcv")Development version
remotes::install_github("mlr-org/mlr3spatiotempcv")
# R Universe Repo
install.packages('mlr3spatiotempcv', mlrorg = 'https://mlr-org.r-universe.dev')Get Started
See the "Get Started" vignette for a quick introduction.
For more detailed information including an usage example see the "Spatiotemporal Analysis" chapter in the mlr3book.
Article "Spatiotemporal Visualization" shows how 3D subplots grids can be created.
Citation
To cite the package in publications, use the output of citation("mlr3spatiotempcv").
Resources
- Recorded talk about mlr3spatiotempcv and mlr3spatial at OpenDataScience Europe Conference 2021 in Wageningen, NL
- List of scientific articles related to spatiotemporal modeling and/or spatial partitioning
Other spatiotemporal resampling packages
This list does not claim to be comprehensive.
(Disclaimer: Because CRAN does not like DOI URLs in their automated checks, direct linking to scientific articles is not possible...)
| Name | Language | Resources |
|---|---|---|
| blockCV | R | CRAN |
| CAST | R | Paper, CRAN |
| ENMeval | R | CRAN |
| spatialsample | R | CRAN |
| sperrorest | R | CRAN |
| Pyspatialml | Python | GitHub |
| spacv | Python | GitHub |
| Museo Toolbox | Python | Paper, GitHub |