Fabien Campillo ; Philippe Cantet ; Rivo Rakotozafy ; Vivien Rossi - Méthodes MCMC en interaction pour l'évaluation de ressources naturelles

arima:1887 - Revue Africaine de la Recherche en Informatique et Mathématiques Appliquées, November 30, 2008, Volume 8, Special Issue CARI'06, 2008 - https://doi.org/10.46298/arima.1887
Méthodes MCMC en interaction pour l'évaluation de ressources naturelles

Authors: Fabien Campillo ; Philippe Cantet ; Rivo Rakotozafy ; Vivien Rossi

Markov chain Monte Carlo (MCMC) methods together with hidden Markov models are extensively used in the Bayesian inference for many scientific fields like environment and ecology. Through simulated examples we show that the speed of convergence of these methods can be very low. In order to improve the convergence properties, we propose a method to make parallel chains interact. We apply this method to a biomass evolution model for fisheries.


Volume: Volume 8, Special Issue CARI'06, 2008
Published on: November 30, 2008
Submitted on: May 28, 2008
Keywords: Bayesian inference,Markov chain Monte Carlo,Inférence bayésienne,Monte Carlo par chaîne de Markov,[MATH.MATH-PR] Mathematics [math]/Probability [math.PR]


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