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.

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Year of publication:	1999
Authors:	Droge, Bernd
Published in:	Statistics & Probability Letters. - Elsevier, ISSN 0167-7152. - Vol. 44.1999, 4, p. 351-357
Publisher:	Elsevier
Keywords:	Cross-validation Full cross-validation Model selection Prediction Asymptotic optimality

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Type of publication:	Article
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005211886