spatialRFThe package spatialRF facilitates fitting spatial regression models on regular or irregular data with Random Forest by generating spatial predictors that allow the model to take into account the spatial structure of the training data. The end goal is minimizing the spatial autocorrelation of the model residuals as much as possible.
For more information visit the spatialRF website.
These versions of spatialRF are available on the BEAR systems (BlueBEAR, BEAR Cloud VMs, and CaStLeS VMs). These will be retained in accordance with our Applications Support and Retention Policy.