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A generalised likelihood framework for partially observed capture-recapture-recovery models

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dc.contributor.authorKing, Ruth
dc.contributor.authorMcCrea, R S
dc.date.accessioned2013-07-25T12:01:01Z
dc.date.available2013-07-25T12:01:01Z
dc.date.issued2014
dc.identifier.citationKing , R & McCrea , R S 2014 , ' A generalised likelihood framework for partially observed capture-recapture-recovery models ' , Statistical Methodology , vol. 17 , pp. 30-45 . https://doi.org/10.1016/j.stamet.2013.07.004en
dc.identifier.issn1572-3127
dc.identifier.otherPURE: 460927
dc.identifier.otherPURE UUID: edf3618a-ab20-4590-bd0e-b3d076caf518
dc.identifier.otherstandrews_research_output: 31580
dc.identifier.otherScopus: 84881512995
dc.identifier.otherWOS: 000329416300004
dc.identifier.urihttps://hdl.handle.net/10023/3877
dc.description.abstractWe provide a closed form likelihood expression for multi-state mark-recapture-recovery data when the state of an individual may be only partially observed. The corresponding su cient statistics are presented in addition to a matrix formulation which facilitates an e cient calculation of the likelihood. This likelihood framework provides a consistent and uni ed framework with many standard models applied to mark-recapture-recovery data as special cases.
dc.language.isoeng
dc.relation.ispartofStatistical Methodologyen
dc.rightsCopyright © 2013 Elsevier B.V. This is the author's version of an article that was accepted for publication in Statistical Methodology. Changes resulting from the publishing process may not be reflected in this document. The published version is available from www.sciencedirect.comen
dc.subjectCapture-recapture-recovery dataen
dc.subjectClosed form likelihooden
dc.subjectMulti-stateen
dc.subjectPartially observed statesen
dc.subjectSufficient statisticsen
dc.subjectQA Mathematicsen
dc.subject.lccQAen
dc.titleA generalised likelihood framework for partially observed capture-recapture-recovery modelsen
dc.typeJournal articleen
dc.description.versionPostprinten
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.identifier.doihttps://doi.org/10.1016/j.stamet.2013.07.004
dc.description.statusPeer revieweden


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