CAST

Supporting functionality to run 'caret' with spatial or spatial-temporal data. 'caret' is a frequently used package for model training and prediction using machine learning. CAST includes functions to improve spatial or spatial-temporal modelling tasks using 'caret'. It includes the newly suggested 'Nearest neighbor distance matching' cross-validation to estimate the performance of spatial prediction models and allows for spatial variable selection to selects suitable predictor variables in view to their contribution to the spatial model performance. CAST further includes functionality to estimate the (spatial) area of applicability of prediction models. Methods are described in Meyer et al. (2018) doi:10.1016/j.envsoft.2017.12.001; Meyer et al. (2019) doi:10.1016/j.ecolmodel.2019.108815; Meyer and Pebesma (2021) doi:10.1111/2041-210X.13650; Milà et al. (2022) doi:10.1111/2041-210X.13851; Meyer and Pebesma (2022) doi:10.1038/s41467-022-29838-9; Linnenbrink et al. (2023) doi:10.5194/egusphere-2023-1308. The package is described in detail in Meyer et al. (2024) doi:10.48550/arXiv.2404.06978.

Last 30 days

This package has been downloaded 1,514 times in the last 30 days. That's enough downloads to impress a room full of undergrads. A commendable achievement indeed. The following heatmap shows the distribution of downloads per day. Yesterday, it was downloaded 55 times.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.

Last 365 days

This package has been downloaded 14,142 times in the last 365 days. The downloads are officially high enough to crash an underfunded departmental server. Quite an accomplishment! The day with the most downloads was Jun 19, 2024 with 119 downloads.

The following line graph shows the downloads per day. You can hover over the graph to see the exact number of downloads per day.