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dc.contributor.authorBorchers, David Louis
dc.contributor.authorZucchini, Walter
dc.contributor.authorHeide-Jørgensen, M.P.
dc.contributor.authorCañadas, A.
dc.contributor.authorLangrock, Roland
dc.identifier.citationBorchers , D L , Zucchini , W , Heide-Jørgensen , M P , Cañadas , A & Langrock , R 2013 , ' Using hidden Markov models to deal with availability bias on line transect surveys ' , Biometrics , vol. 69 , no. 3 , pp. 703-713 .
dc.identifier.otherPURE: 26425234
dc.identifier.otherPURE UUID: d40d7c28-c528-4e29-9a67-454d85d021ee
dc.identifier.otherScopus: 84901231358
dc.identifier.otherORCID: /0000-0002-3944-0754/work/72842444
dc.descriptionThis work was supported by EPSRC grant EP/I000917/1en
dc.description.abstractWe develop estimators for line transect surveys of animals that are stochastically unavailable for detection while within detection range. The detection process is formulated as a hidden Markov model with a binary state-dependent observation model that depends on both perpendicular and forward distances. This provides a parametric method of dealing with availability bias when estimates of availability process parameters are available even if series of availability events themselves are not. We apply the estimators to an aerial and a shipboard survey of whales, and investigate their properties by simulation. They are shown to be more general and more flexible than existing estimators based on parametric models of the availability process. We also find that methods using availability correction factors can be very biased when surveys are not close to being instantaneous, as can estimators that assume temporal independence in availability when there is temporal dependence.
dc.rights© 2013, The International Biometric Society. The final, published version of this article is availble from
dc.subjectAvailability biasen
dc.subjectDetection hazarden
dc.subjectHidden Markov modelen
dc.subjectLine transecten
dc.subjectWildlife surveyen
dc.subjectHA Statisticsen
dc.subjectQH301 Biologyen
dc.titleUsing hidden Markov models to deal with availability bias on line transect surveysen
dc.typeJournal articleen
dc.contributor.institutionUniversity of St Andrews. School of Mathematics and Statisticsen
dc.contributor.institutionUniversity of St Andrews. Scottish Oceans Instituteen
dc.contributor.institutionUniversity of St Andrews. Centre for Research into Ecological & Environmental Modellingen
dc.contributor.institutionUniversity of St Andrews. Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews. Statisticsen
dc.description.statusPeer revieweden

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