STATE-SPACE MODELLING OF DATA ON MARKED INDIVIDUALS
Résumé
State-space models have recently been proposed as a convenient and flexible framework for specifying stochastic models for the dynamics of wild animal populations. Here we focus on the modelling of data on marked individuals which is * Manuscript frequently used in order to estimate demographic parameters while accounting for imperfect detectability. We show how usual models to deal with capture-recapture and ring-recovery data can be fruitfully written as state-space models. An illustration is given using real data and a Bayesian approach using MCMC methods is implemented to estimate the parameters. We give important future developments facilitated by the SSM formulation. Overall, the general state-space modelling framework is shown to have a great potential in population ecology modelling.
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