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

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Documentation for package ‘blockCV’ version 3.1-4

• DESCRIPTION file.
• User guides, package vignettes and other documentation.

Help Pages

blockCV-package	blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation
blockCV	blockCV: Spatial and Environmental Blocking for K-Fold and LOO Cross-Validation
buffering	Use distance (buffer) around records to separate train and test folds
cv_block_size	Explore spatial block size
cv_buffer	Use buffer around records to separate train and test folds (a.k.a. buffered/spatial leave-one-out)
cv_cluster	Use environmental or spatial clustering to separate train and test folds
cv_nndm	Use the Nearest Neighbour Distance Matching (NNDM) to separate train and test folds
cv_plot	Visualising folds created by blockCV in ggplot
cv_similarity	Compute similarity measures to evaluate possible extrapolation in testing folds
cv_spatial	Use spatial blocks to separate train and test folds
cv_spatial_autocor	Measure spatial autocorrelation in spatial response data or predictor raster files
envBlock	Use environmental clustering to separate train and test folds
foldExplorer	Explore the generated folds
rangeExplorer	Explore spatial block size
spatialAutoRange	Measure spatial autocorrelation in the predictor raster files
spatialBlock	Use spatial blocks to separate train and test folds