{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/algorithms-for-fitting-the-constrained-lasso","title":"Algorithms for Fitting the Constrained Lasso","arxiv_id":"1611.01511","date":"2016-10-28","proceeding":null,"authors":["Brian R. Gaines","Hua Zhou"],"abstract":"We compare alternative computing strategies for solving the constrained lasso\nproblem. As its name suggests, the constrained lasso extends the widely-used\nlasso to handle linear constraints, which allow the user to incorporate prior\ninformation into the model. In addition to quadratic programming, we employ the\nalternating direction method of multipliers (ADMM) and also derive an efficient\nsolution path algorithm. Through both simulations and real data examples, we\ncompare the different algorithms and provide practical recommendations in terms\nof efficiency and accuracy for various sizes of data. We also show that, for an\narbitrary penalty matrix, the generalized lasso can be transformed to a\nconstrained lasso, while the converse is not true. Thus, our methods can also\nbe used for estimating a generalized lasso, which has wide-ranging\napplications. Code for implementing the algorithms is freely available in the\nMatlab toolbox SparseReg.","url_abs":"http://arxiv.org/abs/1611.01511v1","url_pdf":"http://arxiv.org/pdf/1611.01511v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"algorithms-for-fitting-the-constrained-lasso","repo_url":"https://github.com/Hua-Zhou/SparseReg","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}