Asymptotic optimality of full cross-validation for selecting linear regression models

For the problem of model selection, full cross-validation has been proposed as an alternative criterion to the traditional cross-validation, particularly in cases where the latter is not well defined. To justify the use of the new proposal we show that under some conditions, both criteria share the same asymptotic optimality property when selecting among linear regression models. (C) 1999 Elsevier Science B.V. All rights reserved.