Exact post-selection inference, with application to the lasso
Jason D. Lee, Dennis L. Sun, Yuekai Sun, Jonathan E. Taylor
The Annals of Statistics · 2016 · Volume 44 · Issue 3
Abstract
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.
Keywords
62E15, 62F03, 62J07, Confidence interval, hypothesis test, Lasso, Model selection
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