Application to fishery stock assessment
نویسندگان
چکیده
We consider a Monte Carlo Markov chain (MCMC) algorithm for fisheries stock assessment. The biomass of this stock at a given year could be modeled as a nonlinear function of the biomass and catch for the two previous years, of different parameters (recruitment, growth rate, natural mortality rate). Given a time series of annual catch and effort data, we would like to achieve the best fitting between the data and a class of non linear/non Gaussian state–space models. RÉSUMÉ. On applique un algorithme de Monte Carlo par Chaîne de Markov (MCMC) à l’évaluation d’un stock de pêcherie. La biomasse de ce stock à une année donnée peut être modélisée comme une fonction non linéaire des biomasses et des prises aux deux années précédentes, ainsi que de différents paramètres (recrutement, taux de croissance, taux de mortalité naturelle). Etant donnée une série temporelle de captures et d’efforts, on souhaite parvenir au meilleur accord entre ces données et une classe de modèles à espace d’état non linéaire/non gaussien.
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تاریخ انتشار 2011