I just updated the r.vif add-on. The add-on let’s you do a step-wise variance inflation factor (VIF) procedure. As explained in more detail here, the VIF can be used to detect multicollinearity in a set of explanatory variables. The step-wise selection procedure provides a way to select a et of variables with sufficient low multicollinearity.

The update should make the computation of VIF much faster. For very large raster layers it is possible to have the VIF computed based on a random subset of raster cells. There is also a low-memory option. This allows one to run this add-on with much larger data sets. But, as explained in the r.vif manual page, it also runs considerably slower.