Exact Post - Selection Inference with the Lasso
نویسندگان
چکیده
We develop a framework for post-selection inference with the lasso. At the core of our framework is a result that characterizes the exact (non-asymptotic) distribution of linear combinations/contrasts of truncated normal random variables. This result allows us to (i) obtain honest confidence intervals for the selected coefficients that account for the selection procedure, and (ii) devise a test statistic that has an exact (non-asymptotic) Unif(0, 1) distribution when all relevant variables have been included in the model.
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تاریخ انتشار 2014