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Title:Asymptotic optimality of full cross-validation for selecting linear regression models PDF Logo
Authors:Droge, Bernd
Issue Date:1997
Series/Report no.:Discussion Papers, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes 1997,5
Abstract: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.
Subjects:prediction
model selection
asymptotic optimality
Cross-validation
full cross-validation
Persistent Identifier of the first edition:urn:nbn:de:kobv:11-10063605
Document Type:Working Paper
Appears in Collections:Discussion Papers, SFB 373, HU Berlin

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