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Analyse bayésienne de modèles markoviens d'évolution de ressources naturelles

Fabien Campillo 1 Rivo Rakotozafy 2 Vivien Rossi 1 
1 ASPI - Applications of interacting particle systems to statistics
UR1 - Université de Rennes 1, Inria Rennes – Bretagne Atlantique , CNRS - Centre National de la Recherche Scientifique : UMR6074
Abstract : One applies Monte Carlo methods to state sapce models with unknown parameters. The first one is a Monte Carlo Markov Chain algorithm. The second one is the particle filtering. We compare these methods applied to a biomass evolution model for fisheries.
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  • HAL Id : inria-00506586, version 1


Fabien Campillo, Rivo Rakotozafy, Vivien Rossi. Analyse bayésienne de modèles markoviens d'évolution de ressources naturelles. International African Conference on Research in Computer Science and Applied mathematics (CARI'06), Nov 2006, Cotonou, Bénin. ⟨inria-00506586⟩



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