Applications of hidden hybrid Markov/semi-Markov models: from stopover duration to breeding success dynamics
Article first published online: 20 FEB 2014
© 2014 The Authors. Ecology and Evolution published by John Wiley & Sons Ltd.
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Ecology and Evolution
Volume 4, Issue 6, pages 817–826, March 2014
How to Cite
Ecology and Evolution 2014; 4(6):817–826
- Issue published online: 18 MAR 2014
- Article first published online: 20 FEB 2014
- Manuscript Accepted: 4 JAN 2014
- Manuscript Received: 12 DEC 2013
- Montpellier sud de France University
Usually in capture–recapture, a model parameter is time or time since first capture 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 previous 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.