Exact post-selection inference, with application to the lasso

Autor:	Lee, Jason D., Sun, Dennis L., Sun, Yuekai, Taylor, Jonathan E.
Rok vydání:	2013
Předmět:	Mathematics - Statistics Theory Statistics - Methodology Statistics - Machine Learning
Zdroj:	Annals of Statistics 2016, Vol. 44, No. 3, 907-927
Druh dokumentu:	Working Paper
DOI:	10.1214/15-AOS1371
Popis:	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. Comment: Published at http://dx.doi.org/10.1214/15-AOS1371 in the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1311.6238 Zobrazit plný text záznamu View this record from Arxiv