# The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R

## Author(s): Li, Xingguo; Zhao, Tuo; Yuan, Xiaoming; Liu, Han

To refer to this page use: http://arks.princeton.edu/ark:/88435/pr1kg4j
DC FieldValueLanguage
dc.contributor.authorLi, Xingguo-
dc.contributor.authorZhao, Tuo-
dc.contributor.authorYuan, Xiaoming-
dc.contributor.authorLiu, Han-
dc.date.accessioned2021-10-11T14:17:07Z-
dc.date.available2021-10-11T14:17:07Z-
dc.date.issued2015en_US
dc.identifier.citationLi, Xingguo, Tuo Zhao, Xiaoming Yuan, and Han Liu. "The flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in R." Journal of Machine Learning Research 16, no. 18 (2015): 553-557.en_US
dc.identifier.issn1532-4435-
dc.identifier.urihttp://www.jmlr.org/papers/v16/li15a.html-
dc.identifier.urihttp://arks.princeton.edu/ark:/88435/pr1kg4j-
dc.description.abstractThis paper describes an R package named flare, which implements a family of new high dimensional regression methods (LAD Lasso, SQRT Lasso, ℓq Lasso, and Dantzig selector) and their extensions to sparse precision matrix estimation (TIGER and CLIME). These methods exploit different nonsmooth loss functions to gain modeling flexibility, estimation robustness, and tuning insensitiveness. The developed solver is based on the alternating direction method of multipliers (ADMM). The package flare is coded in double precision C, and called from R by a user-friendly interface. The memory usage is optimized by using the sparse matrix output. The experiments show that flare is efficient and can scale up to large problems.en_US
dc.format.extent553 - 557en_US
dc.languageengen_US
dc.language.isoen_USen_US
dc.relation.ispartofJournal of Machine Learning Researchen_US
dc.rightsFinal published version. Article is made available in OAR by the publisher's permission or policy.en_US
dc.titleThe flare Package for High Dimensional Linear Regression and Precision Matrix Estimation in Ren_US
dc.typeJournal Articleen_US
dc.identifier.eissn1533-7928-
pu.type.symplectichttp://www.symplectic.co.uk/publications/atom-terms/1.0/journal-articleen_US

Files in This Item:
File Description SizeFormat