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Applications of hidden hybrid Markov/semi-Markov models: from stopover duration to breeding success dynamics

Rémi Choquet 1 Arnaud Béchet 2 yann Guédon 3, 4 
3 VIRTUAL PLANTS - Modeling plant morphogenesis at different scales, from genes to phenotype
CRISAM - Inria Sophia Antipolis - Méditerranée , INRA - Institut National de la Recherche Agronomique, UMR AGAP - Amélioration génétique et adaptation des plantes méditerranéennes et tropicales
Abstract : Usually in capture–recapture, a model parameter is time or time since first cap-ture dependent. However, the case where the probability of staying in one state depends on the time spent in that particular state is not rare. Hidden Markov models are not appropriate to manage these situations. A more convenient approach would be to consider models that incorporate semi-Markovian states which explicitly define the waiting time distribution and have been used in pre-vious biologic studies as a convenient framework for modeling the time spent in a given physiological state. Here, we propose hidden Markovian models that combine several nonhomogeneous Markovian states with one semi-Markovian state and which (i) are well adapted to imperfect and variable detection and (ii) allow us to consider time, time since first capture, and time spent in one state effects. Implementation details depending on the number of semi-Markovian states are discussed. From a user's perspective, the present approach enhances the toolbox for analyzing capture–recapture data. We then show the potential of this framework by means of two ecological examples: (i) stopover duration and (ii) breeding success dynamics.
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Submitted on : Wednesday, November 19, 2014 - 1:30:26 PM
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Rémi Choquet, Arnaud Béchet, yann Guédon. Applications of hidden hybrid Markov/semi-Markov models: from stopover duration to breeding success dynamics. Ecology and Evolution, Wiley Open Access, 2014, 4 (6), pp.817 - 826. ⟨10.1002/ece3.962⟩. ⟨hal-01084498⟩



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