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.

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Type of publication:	Book / Working Paper
Language:	English
Notes:	Bachoc, Francois and Leeb, Hannes and Pötscher, Benedikt M. (2014): Valid confidence intervals for post-model-selection predictors.
Classification:	C1 - Econometric and Statistical Methods: General ; C2 - Econometric Methods: Single Equation Models ; C52 - Model Evaluation and Testing
Source:	BASE

Persistent link: https://ebvufind01.dmz1.zbw.eu/10015245408