4.6 Article

EXACT POST-SELECTION INFERENCE, WITH APPLICATION TO THE LASSO

期刊

ANNALS OF STATISTICS
卷 44, 期 3, 页码 907-927

出版社

INST MATHEMATICAL STATISTICS
DOI: 10.1214/15-AOS1371

关键词

Lasso; confidence interval; hypothesis test; model selection

资金

  1. National Defense Science and Engineering Graduate Fellowship
  2. Stanford Graduate Fellowship
  3. Ric Weiland Graduate Fellowship
  4. Stanford Genome Training Program (SGTP
  5. NIH/NHGRI)
  6. NIH [U01GM102098]
  7. NSF [DMS-12-08857]
  8. AFOSR [113039]
  9. Direct For Mathematical & Physical Scien
  10. Division Of Mathematical Sciences [1208857] Funding Source: National Science Foundation

向作者/读者索取更多资源

We develop a general approach to valid inference after model selection. At the core of our framework is a result that characterizes. the distribution of a post-selection estimator conditioned on the selection event. We specialize the approach to model selection by the lasso to form valid confidence intervals for the selected coefficients and test whether all relevant variables have been included in the model.

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