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Sonderforschungsbereich 373: Quantification and Simulation of Economic Processes, Humboldt-Universität Berlin >
Discussion Papers, SFB 373, HU Berlin >
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http://hdl.handle.net/10419/66243
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| Title: | | Asymptotic optimality of full cross-validation for selecting linear regression models  |
| 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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