Exact post-selection inference, with application to the lasso
J. Lee, D. Sun, Y. Sun, and J. Taylor. (2013)cite arxiv:1311.6238Comment: 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).
DOI: 10.1214/15-AOS1371
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.
Description
[1311.6238] Exact post-selection inference, with application to the lasso
cite arxiv:1311.6238Comment: 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)
%0 Generic
%1 lee2013exact
%A Lee, Jason D.
%A Sun, Dennis L.
%A Sun, Yuekai
%A Taylor, Jonathan E.
%D 2013
%K estimation-after-selection frequentist lasso statistics
%R 10.1214/15-AOS1371
%T Exact post-selection inference, with application to the lasso
%U http://arxiv.org/abs/1311.6238
%X 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.
@misc{lee2013exact,
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.},
added-at = {2019-05-11T07:42:45.000+0200},
author = {Lee, Jason D. and Sun, Dennis L. and Sun, Yuekai and Taylor, Jonathan E.},
biburl = {https://www.bibsonomy.org/bibtex/2805db0f493d127699c38a593494ade30/shabbychef},
description = {[1311.6238] Exact post-selection inference, with application to the lasso},
doi = {10.1214/15-AOS1371},
interhash = {0c09f139d95cc88edf064fd954c2c227},
intrahash = {805db0f493d127699c38a593494ade30},
keywords = {estimation-after-selection frequentist lasso statistics},
note = {cite arxiv:1311.6238Comment: 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)},
timestamp = {2019-05-11T07:42:45.000+0200},
title = {Exact post-selection inference, with application to the lasso},
url = {http://arxiv.org/abs/1311.6238},
year = 2013
}