Valid confidence intervals for post-model-selection predictors

Francois Bachoc, Hannes Leeb and Benedikt Pötscher

MPRA Paper from University Library of Munich, Germany

Abstract: We consider inference post-model-selection in linear regression. In this setting, Berk et al.(2013) recently introduced a class of confidence sets, the so-called PoSI intervals, that cover a certain non-standard quantity of interest with a user-specified minimal coverage probability, irrespective of the model selection procedure that is being used. In this paper, we generalize the PoSI intervals to post-model-selection predictors.

Keywords: Inference post-model-selection; confidence intervals; optimal post-model-selection predictors; non-standard targets; linear regression (search for similar items in EconPapers)
JEL-codes: C1 C2 C52 (search for similar items in EconPapers)
Date: 2014-12
New Economics Papers: this item is included in nep-ecm
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Citations: View citations in EconPapers (1)

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https://mpra.ub.uni-muenchen.de/69352/1/MPRA_paper_69352.pdf revised version (application/pdf)
https://mpra.ub.uni-muenchen.de/76453/9/MPRA_paper_76453.pdf revised version (application/pdf)

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