The final prediction error (FPE) criterion has been used widely in model selection. The criterion for a linear regression model with k parameters can be written as RSS(k) + [lambda]k2, where RSS(k) is the residual sums of squares, 2 is an unbiased estimate of the error variance and [lambda] is a...