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bioRxiv · 10.1101/357798

blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models

Valavi, R.·Elith, J.·Lahoz-Monfort, J. J.·Guillera-Arroita, G.
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Abstract

O_LIWhen applied to structured data, conventional random cross-validation techniques can lead to underestimation of prediction error, and may result in inappropriate model selection.\nC_LIO_LIWe present the R package blockCV, a new toolbox for cross-validation of species distribution modelling.\nC_LIO_LIThe package can generate spatially or environmentally separated folds. It includes tools to measure spatial autocorrelation ranges in candidate covariates, providing the user with insights into the spatial structure in these data. It also offers interactive graphical capabilities for creating spatial blocks and exploring data folds.\nC_LIO_LIPackage blockCV enables modellers to more easily implement a range of evaluation approaches. It will help the modelling community learn more about the impacts of evaluation approaches on our understanding of predictive performance of species distribution models.\nC_LI

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Valavi, R., Elith, J., Lahoz-Monfort, J. J., Guillera-Arroita, G.. 2018-06-28. blockCV: an R package for generating spatially or environmentally separated folds for k-fold cross-validation of species distribution models. https://doi.org/10.1101/357798

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