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

For the problem of model selection, full cross-validation has been proposed as alternative criterion to the traditional cross-validation, particularly in cases where the latter one 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:	1997
Authors:	Droge, Bernd
Institutions:	Sonderforschungsbereich 373, Quantifikation und Simulation ökonomischer Prozesse, Wirtschaftswissenschaftliche Fakultät
Subject:	prediction \| model selection \| asymptotic optimality \| Cross-validation \| full cross-validation

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Extent:	application/pdf
Series:	SFB 373 Discussion Papers.
Type of publication:	Book / Working Paper
Notes:	Number 1997,5
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10010956413