Analyse bayésienne de modèles markoviens d'évolution de ressources naturelles
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.
Domains
Probability [math.PR]
Origin : Publisher files allowed on an open archive
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