Regression shrinkage and selection via the lasso: a retrospective

• 成果类型: Article
• 署名作者: Tibshirani, Robert
• 署名单位: Stanford University
• 刊物名称: JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
• ISSN/ISSBN: 1369-7412
• DOI: 10.1111/j.1467-9868.2011.00771.x
• 发表日期: 2011
• 页码: 273-282
• 关键词: GENERALIZED LINEAR-MODELS; variable selection; descent method; regularization; sparsity; algorithms; mixture

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.