Valid confidence intervals for post-model-selection predictors

Bachoc, Francois and Leeb, Hannes and Pötscher, Benedikt M. (2014): Valid confidence intervals for post-model-selection predictors.

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.

• Item Type: MPRA Paper
• Language: English
• Keywords: Inference post-model-selection, confidence intervals, optimal post-model-selection predictors, non-standard targets, linear regression
• Subjects: C - Mathematical and Quantitative Methods > C1 - Econometric and Statistical Methods and Methodology: General; C - Mathematical and Quantitative Methods > C2 - Single Equation Models ; Single Variables; C - Mathematical and Quantitative Methods > C5 - Econometric Modeling > C52 - Model Evaluation, Validation, and Selection

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