On the "degrees of freedom" of the lasso

dc.creatorZou, Hui
dc.creatorHastie, Trevor
dc.creatorTibshirani, Robert
dc.date2007-12-06
dc.date.accessioned2026-07-07T08:49:27Z
dc.date.available2026-07-07T08:49:27Z
dc.descriptionWe study the effective degrees of freedom of the lasso in the framework of Stein's unbiased risk estimation (SURE). We show that the number of nonzero coefficients is an unbiased estimate for the degrees of freedom of the lasso--a conclusion that requires no special assumption on the predictors. In addition, the unbiased estimator is shown to be asymptotically consistent. With these results on hand, various model selection criteria--$C_p$, AIC and BIC--are available, which, along with the LARS algorithm, provide a principled and efficient approach to obtaining the optimal lasso fit with the computational effort of a single ordinary least-squares fit.
dc.descriptionPublished in at http://dx.doi.org/10.1214/009053607000000127 the Annals of Statistics (http://www.imstat.org/aos/) by the Institute of Mathematical Statistics (http://www.imstat.org)
dc.identifierhttps://arxiv.org/abs/0712.0881
dc.identifierhttp://arxiv.org/abs/0712.0881
dc.identifierAnnals of Statistics 2007, Vol. 35, No. 5, 2173-2192
dc.identifierdoi:10.1214/009053607000000127
dc.identifier.urihttp://salesiana.dossiersoluciones.com/handle/123456789/144302
dc.subjectStatistics Theory
dc.subject62J05, 62J07, 90C46 (Primary)
dc.titleOn the "degrees of freedom" of the lasso
dc.typetext

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