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Journal articles

Parameter Redundancy in Multistate Capture-Recapture Models

Abstract : Multistate capture-recapture models are a powerful tool to address a variety of biological questions concerning dispersal and/or individual variability in wild animal populations. However, biologically meaningful models are often over-parameterized and consequently some parameters cannot be estimated separately. Identifying which quantities are separately estimable is crucial for proper model selection based upon likelihood tests or information criteria and for the interpretation of the estimates obtained. We show how to investigate parameter redundancy in multistate capture-recapture models, based on formal methods initially proposed by Catchpole and his associates for exponential family distributions (Catchpole, Freeman and Morgan, 1996. Journal of the Royal Statistical Society Series B 58, 763-774). We apply their approach to three models of increasing complexity.
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Contributor : Olivier Gimenez Connect in order to contact the contributor
Submitted on : Wednesday, January 19, 2022 - 8:38:29 AM
Last modification on : Wednesday, March 23, 2022 - 12:08:29 PM
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Olivier Gimenez, Rémi Choquet, Jean-Dominique Lebreton. Parameter Redundancy in Multistate Capture-Recapture Models. Biometrical Journal, Wiley-VCH Verlag, 2003, 45 (6), pp.704-722. ⟨10.1002/bimj.200390043⟩. ⟨hal-03515251⟩



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