gcv matches those for the
locfit or locfit.raw functions.
The fit is not returned; instead, the returned object contains
Wahba's generalized cross-validation score for the fit. The GCV score is exact (up to numerical roundoff) if the
ev="data" argument is provided. Otherwise, the residual
sum-of-squares and degrees of freedom are computed using locfit's
standard interpolation based approximations.
For likelihood models, GCV is computed using -2 times the log-likelihood in place of the residual sum of squares; I know of no results validating this interpretation.
gcv(x, ...)locfit,
locfit.raw,
gcvplot