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VALID CONFIDENCE INTERVALS FOR POST-MODEL-SELECTION PREDICTORS
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DOI：10.1214/18-AOS1721.png)
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摘要
En 中文
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.
Keyword:
Inference post-model-selection
confidence intervals
optimal post-model-selection predictors
nonstandard targets
linear regression
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2.8K
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