Regression shrinkage and selection via the lasso: a retrospective

被引:1787
作者
Tibshirani, Robert [1 ]
机构
[1] Stanford Univ, Dept Hlth Res & Policy, Stanford, CA 94305 USA
关键词
l(1)-penalty; Penalization; Regularization; GENERALIZED LINEAR-MODELS; VARIABLE SELECTION; DESCENT METHOD; REGULARIZATION; SPARSITY; ALGORITHMS; MIXTURE;
D O I
10.1111/j.1467-9868.2011.00771.x
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
In the paper I give a brief review of the basic idea and some history and then discuss some developments since the original paper on regression shrinkage and selection via the lasso.
引用
收藏
页码:273 / 282
页数:10
相关论文
共 66 条
[41]   p-Values for High-Dimensional Regression [J].
Meinshausen, Nicolai ;
Meier, Lukas ;
Buehlmann, Peter .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2009, 104 (488) :1671-1681
[42]   On the LASSO and its dual [J].
Osborne, MR ;
Presnell, B ;
Turlach, BA .
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2000, 9 (02) :319-337
[43]   The Bayesian Lasso [J].
Park, Trevor ;
Casella, George .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2008, 103 (482) :681-686
[44]   Block coordinate relaxation methods for nonparametric wavelet denoising [J].
Sardy, S ;
Bruce, AG ;
Tseng, P .
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS, 2000, 9 (02) :361-379
[45]   On the statistical analysis of smoothing by maximizing dirty Markov random field posterior distributions [J].
Sardy, S ;
Tseng, P .
JOURNAL OF THE AMERICAN STATISTICAL ASSOCIATION, 2004, 99 (465) :191-204
[46]  
SCHELLDORFER J, 2011, SCAND J STA IN PRESS
[47]  
STADLER N, 2011, STAT COMPUT IN PRESS
[48]  
Städler N, 2010, TEST-SPAIN, V19, P209, DOI 10.1007/s11749-010-0197-z
[49]   Sparsity and smoothness via the fused lasso [J].
Tibshirani, R ;
Saunders, M ;
Rosset, S ;
Zhu, J ;
Knight, K .
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2005, 67 :91-108