Valid confidence intervals for post-model-selection predictors

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.

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Year of publication:	2014-12
Authors:	Bachoc, Francois ; Leeb, Hannes ; Pötscher, Benedikt M.
Institutions:	Volkswirtschaftliche Fakultät, Ludwig-Maximilians-Universität München
Subject:	Inference post-model-selection \| confidence intervals \| optimal post-model-selection predictors \| non-standard targets \| linear regression

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Extent:	application/pdf
Series:	MPRA Paper.
Type of publication:	Book / Working Paper
Classification:	C1 - Econometric and Statistical Methods: General ; C2 - Econometric Methods: Single Equation Models ; C52 - Model Evaluation and Testing
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011109357