Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/66243 
Authors: 
Year of Publication: 
1997
Series/Report no.: 
SFB 373 Discussion Paper No. 1997,5
Publisher: 
Humboldt University of Berlin, Interdisciplinary Research Project 373: Quantification and Simulation of Economic Processes, Berlin
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: 
Document Type: 
Working Paper

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