Package: blockCV 3.2-0

blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation

Creating spatially or environmentally separated folds for cross-validation to provide a robust error estimation in spatially structured environments; Investigating and visualising the effective range of spatial autocorrelation in continuous raster covariates and point samples to find an initial realistic distance band to separate training and testing datasets spatially described in Valavi, R. et al. (2019) <doi:10.1111/2041-210X.13107>.

Authors:Roozbeh Valavi [aut, cre], Jane Elith [aut], José Lahoz-Monfort [aut], Ian Flint [aut], Gurutzeta Guillera-Arroita [aut]

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manual.pdf |manual.html✨
DESCRIPTION
card.svg |card.png
blockCV/json (API)

# Install 'blockCV' in R:
install.packages('blockCV', repos = c('https://rvalavi.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/rvalavi/blockcv/issues

Uses libs:
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

cross-validationspatialspatial-cross-validationspatial-modellingspecies-distribution-modellingcpp

11.43 score 122 stars 4 packages 444 scripts 5.9k downloads 5 mentions 13 exports 45 dependencies

Last updated from:cf04539ae6. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK186
linux-devel-x86_64OK175
source / vignettesOK300
linux-release-arm64OK190
linux-release-x86_64OK204
macos-release-arm64OK171
macos-release-x86_64OK266
macos-oldrel-arm64OK118
macos-oldrel-x86_64OK266
windows-develOK167
windows-releaseOK144
windows-oldrelOK133
wasm-releaseOK155

Exports:bufferingcv_block_sizecv_buffercv_clustercv_nndmcv_plotcv_similaritycv_spatialcv_spatial_autocorenvBlockrangeExplorerspatialAutoRangespatialBlock

Dependencies:abindautomapclassclassIntclicowplotcpp11DBIe1071farverFNNggplot2gluegstatgtableintervalsisobandKernSmoothlabelinglatticelifecycleMASSplyrproxyR6RColorBrewerRcppreshaperlangs2S7scalessfsftimespspacetimestarsterraunitsvctrsviridisLitewithrwkxtszoo

blockCV introduction: how to create block cross-validation folds
Introduction | New updates of the version 3.0 | Installation | Package data | Block cross-validation strategies | Spatial blocks | Spatial and environemntal clustering | Buffering LOO (also known as Spatial LOO) | Nearest Neighbour Distance Matching (NNDM) LOO | Visualising the folds | Check similarity | Estimating size: the effective range of spatial autocorrelation | References:
Rendered fromtutorial_1.Rmdusingknitr::rmarkdown

Last update: 2025-08-15
Started: 2023-01-29

Block cross-validation for species distribution modelling
Introduction | Reading and plotting data | Generating block CV folds | Evaluating SDMs with block cross-validation: examples | Using blockCV with Random Forest model | Using blockCV in biomod2 package | References:
Rendered fromtutorial_2.Rmdusingknitr::rmarkdown

Last update: 2025-06-23
Started: 2023-01-29