Abstract
We consider inference post-model-selection in linear regression. In this setting, Berk et al. [Ann. Statist. 41 (2013a) 802–837] recently introduced a class of confidence sets, the so-called PoSI intervals, that cover a certain nonstandard 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 confidence intervals for post-model-selection predictors.
Citation
François Bachoc. Hannes Leeb. Benedikt M. Pötscher. "Valid confidence intervals for post-model-selection predictors." Ann. Statist. 47 (3) 1475 - 1504, June 2019. https://doi.org/10.1214/18-AOS1721
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