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Sparsity and smoothness via the fused lasso
dc.contributor.authorTibshirani, Roberten_US
dc.contributor.authorSaunders, Michaelen_US
dc.contributor.authorRosset, Saharonen_US
dc.contributor.authorZhu, Jien_US
dc.contributor.authorKnight, Keithen_US
dc.date.accessioned2010-06-01T20:29:41Z
dc.date.available2010-06-01T20:29:41Z
dc.date.issued2005-02en_US
dc.identifier.citationTibshirani, Robert; Saunders, Michael; Rosset, Saharon; Zhu, Ji; Knight, Keith (2005). "Sparsity and smoothness via the fused lasso." Journal of the Royal Statistical Society: Series B (Statistical Methodology) 67(1): 91-108. <http://hdl.handle.net/2027.42/73606>en_US
dc.identifier.issn1369-7412en_US
dc.identifier.issn1467-9868en_US
dc.identifier.urihttps://hdl.handle.net/2027.42/73606
dc.format.extent304273 bytes
dc.format.extent3109 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.publisherBlackwell Publishing Ltden_US
dc.rights2005 Royal Statistical Societyen_US
dc.subject.otherFused Lassoen_US
dc.subject.otherGene Expressionen_US
dc.subject.otherLassoen_US
dc.subject.otherLeast Squares Regressionen_US
dc.subject.otherProtein Mass Spectroscopyen_US
dc.subject.otherSparse Solutionsen_US
dc.subject.otherSupport Vector Classifieren_US
dc.titleSparsity and smoothness via the fused lassoen_US
dc.typeArticleen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumUniversity of Michigan, Ann Arbor, USAen_US
dc.contributor.affiliationotherStanford University, USAen_US
dc.contributor.affiliationotherIBM T. J. Watson Research Center, Yorktown Heights, USAen_US
dc.contributor.affiliationotherUniversity of Toronto, Canadaen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/73606/1/j.1467-9868.2005.00490.x.pdf
dc.identifier.doi10.1111/j.1467-9868.2005.00490.xen_US
dc.identifier.sourceJournal of the Royal Statistical Society: Series B (Statistical Methodology)en_US
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dc.owningcollnameInterdisciplinary and Peer-Reviewed


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