  A Two-Stage approach enables researchers to make optimal non-linear
predictions via Generalized Ridge Regression using models that contain two or
more x-predictor variables and make only realistic minimal assumptions. The
optimal regression coefficient estimates that result are either unbiased or
most likely to have mininal MSE risk under Normal distribution theory. All
necessary calculations and graphical displays are generated using current
versions of CRAN R-packages. A numerical example using the "corrected"
USArrests data.frame introduces and illustrates this new robust statistical
methodology. While applying this strategy to regression models with several
hundred observations is straight-forward, the computations required in such
cases can be extensive.
