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Communication Dans Un Congrès Année : 2004

{MCMC} for non linear/non {Gaussian} state-space models: Application to fishery stock assessment

Résumé

We consider a Monte Carlo Markov chain (MCMC) algorithm for fisheries stock assess- ment. 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, nat- ural 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.
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Dates et versions

hal-00652092 , version 1 (14-12-2011)

Identifiants

  • HAL Id : hal-00652092 , version 1

Citer

Fabien Campillo, Rivo Rakotozafy. {MCMC} for non linear/non {Gaussian} state-space models: Application to fishery stock assessment. 7th African Conference on Research in Computer Science, Nov 2004, Hammamet, Tunisia. ⟨hal-00652092⟩
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