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dc.contributor.authorFang, Yixin
dc.contributor.authorWang, Junhui
dc.date.accessioned2011-05-27T16:19:09Z
dc.date.available2011-05-27T16:19:09Z
dc.date.issued2011-06-01
dc.identifier.bibliographicCitationFang, Y. X. & Wang, J. H. 2011. Penalized Cluster Analysis With Applications to Family Data. Computational Statistics & Data Analysis, 55(6): 2128-2136. DOI: 10.1016/j.csda.2011.01.004en
dc.identifier.issn0167-9473
dc.identifier.otherDOI: 10.1016/j.csda.2011.01.004
dc.identifier.urihttp://hdl.handle.net/10027/7733
dc.descriptionNOTICE: this is the author’s version of a work that was accepted for publication in Computational Statistics and Data Analysis. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computational Statistics and Data Analysis, [Vol 55, Issue 6, (June 1, 2011)] DOI: 10.1016/j.csda.2011.01.004. The original publication is available at www.elsevier.com.en
dc.description.abstractCluster analysis is the assignment of observations into clusters so that observations in the same cluster are similar in some sense, and many clustering methods have been developed. However, these methods cannot be applied to family data, which possess intrinsic familial structure. To take the familial structure into account, we propose a form of penalized cluster analysis with a tuning parameter controlling its influence. The tuning parameter can be selected based on the concept of clustering stability. The method can also be applied to other cluster data such as panel data. The method is illustrated via simulations and an application to a family study of asthma.en
dc.description.sponsorshipThe asthma dataset was originally collected as part of the Collaborative Study on the Genetics of Asthma sponsored by the National Heart, Lung, and Blood Institute.en
dc.language.isoen_USen
dc.publisherElsevieren
dc.subjectconsistencyen
dc.subjectcross-validationen
dc.subjectkinshipen
dc.subjectk-meansen
dc.subjectstabilityen
dc.titlePenalized Cluster Analysis With Applications to Family Dataen
dc.typeArticleen


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