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Conference papers
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.
Cited literature [9 references]
https://hal.inria.fr/inria-00506586
Contributor : Fabien Campillo Connect in order to contact the contributor
Submitted on : Wednesday, July 28, 2010 - 12:25:57 PM
Last modification on : Friday, January 21, 2022 - 4:12:58 AM
Long-term archiving on: : Friday, October 29, 2010 - 10:35:49 AM
Contributor : Fabien Campillo Connect in order to contact the contributor
Submitted on : Wednesday, July 28, 2010 - 12:25:57 PM
Last modification on : Friday, January 21, 2022 - 4:12:58 AM
Long-term archiving on: : Friday, October 29, 2010 - 10:35:49 AM
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campillo2006a.pdf
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