Another Example of Nonparametric Generalized Ridge Regression

The Two-Stage approach to optimal \textit{non-linear} predictions via Generalized Ridge Regression is again illustrated. This time, we use a model with six $x-$predictors and more than $2,500$ observations. Unbiased estimates and predictions are then compared with their corresponding ``optimally biased'' estimates and predictions most likely to have minimal MSE risk under Normal distribution theory. Again, we find that lower residual standard errors and lower MSE risks relative to those lower errors result.