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Implementing semiparametric density estimation
dc.contributor.authorFaraway, Julian J.en_US
dc.date.accessioned2006-04-10T13:40:55Z
dc.date.available2006-04-10T13:40:55Z
dc.date.issued1990-07en_US
dc.identifier.citationFaraway, Julian (1990/07)."Implementing semiparametric density estimation." Statistics &amp; Probability Letters 10(2): 141-143. <http://hdl.handle.net/2027.42/28492>en_US
dc.identifier.urihttp://www.sciencedirect.com/science/article/B6V1D-45DB18G-3F/2/cfb8696227efaa58159276ee6c32bb2aen_US
dc.identifier.urihttps://hdl.handle.net/2027.42/28492
dc.description.abstractA semiparametric estimate of a density may be formed via the convex combination of a parametric and a nonparametric density estimate. It is shown that the some trimming is often necessary to obtain an appropriate proportion of these estimates.en_US
dc.format.extent216715 bytes
dc.format.extent3118 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypetext/plain
dc.language.isoen_US
dc.publisherElsevieren_US
dc.titleImplementing semiparametric density estimationen_US
dc.typeArticleen_US
dc.rights.robotsIndexNoFollowen_US
dc.subject.hlbsecondlevelStatistics and Numeric Dataen_US
dc.subject.hlbsecondlevelMathematicsen_US
dc.subject.hlbtoplevelSocial Sciencesen_US
dc.subject.hlbtoplevelScienceen_US
dc.description.peerreviewedPeer Revieweden_US
dc.contributor.affiliationumDepartment of Statistics, University of Michigan, Ann Arbor, MI 48109-1027, USAen_US
dc.description.bitstreamurlhttp://deepblue.lib.umich.edu/bitstream/2027.42/28492/1/0000289.pdfen_US
dc.identifier.doihttp://dx.doi.org/10.1016/0167-7152(90)90009-Ven_US
dc.identifier.sourceStatistics &amp; Probability Lettersen_US
dc.owningcollnameInterdisciplinary and Peer-Reviewed


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