Detail
Valid Confidence Intervals for Post-Model-Selection Predictors
- Author(s)
- Francois Bachoc, Hannes Leeb, Benedikt Pötscher
- 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.
- Organisation(s)
- Department of Statistics and Operations Research, Research Network Data Science
- Journal
- Annals of Statistics
- Volume
- 47
- Pages
- 1475-1504
- No. of pages
- 30
- ISSN
- 0090-5364
- DOI
- https://doi.org/10.1214/18-AOS1721
- Publication date
- 06-2019
- Peer reviewed
- Yes
- Austrian Fields of Science 2012
- 502025 Econometrics, 101029 Mathematical statistics
- Keywords
- ASJC Scopus subject areas
- Statistics and Probability, Statistics, Probability and Uncertainty
- Portal url
- https://ucris.univie.ac.at/portal/en/publications/valid-confidence-intervals-for-postmodelselection-predictors(61f184a1-8509-4d44-a4dc-5060ea796ac7).html