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dc.contributor.authorHart, Jeffrey D.
dc.contributor.authorCañette, Isabel
dc.date.accessioned2016-02-25T13:50:54Z
dc.date.available2016-02-25T13:50:54Z
dc.date.issued2011-01
dc.identifier.citationHart JD, Cañette I (2011) Nonparametric Estimation of Distributions in Random Effects Models. Journal of Computational and Graphical Statistics 20: 461–478. Available: http://dx.doi.org/10.1198/jcgs.2011.09121.
dc.identifier.issn1061-8600
dc.identifier.issn1537-2715
dc.identifier.doi10.1198/jcgs.2011.09121
dc.identifier.urihttp://hdl.handle.net/10754/598999
dc.description.abstractWe propose using minimum distance to obtain nonparametric estimates of the distributions of components in random effects models. A main setting considered is equivalent to having a large number of small datasets whose locations, and perhaps scales, vary randomly, but which otherwise have a common distribution. Interest focuses on estimating the distribution that is common to all datasets, knowledge of which is crucial in multiple testing problems where a location/scale invariant test is applied to every small dataset. A detailed algorithm for computing minimum distance estimates is proposed, and the usefulness of our methodology is illustrated by a simulation study and an analysis of microarray data. Supplemental materials for the article, including R-code and a dataset, are available online. © 2011 American Statistical Association.
dc.description.sponsorshipThe work of Professor Hart was supported by NSF grant DMS-0604801 and by Award no. KUS-C1-016-04, made by King Abdullah University of Science and Technology (KAUST).
dc.publisherInforma UK Limited
dc.subjectCharacteristic function
dc.subjectIdentifiability
dc.subjectMinimum distance estimation
dc.subjectQuantile function
dc.titleNonparametric Estimation of Distributions in Random Effects Models
dc.typeArticle
dc.identifier.journalJournal of Computational and Graphical Statistics
dc.contributor.institutionTexas A and MUniversity, TX, 77843, United States
dc.contributor.institutionStataCorp, College Station, United States
kaust.grant.numberKUS-C1-016-04


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