{MCMC} for non linear/non {Gaussian} state-space models: Application to fishery stock assessment
Abstract
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.
Domains
Probability [math.PR]
Origin : Explicit agreement for this submission
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