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Communication Dans Un Congrès Année : 2008

Computational probability modeling and Bayesian inference

Rivo R. Rakotozafy
  • Fonction : Auteur
Vivien V. Rossi

Résumé

Computational probabilistic modeling and Bayesian inference has met a great success over the past fifteen years through the development of Monte Carlo methods and the ever increasing performance of computers. Through methods such as Monte Carlo Markov chain and sequential Monte Carlo Bayesian inference effectively combines with Markovian modelling. This approach has been very successful in ecology and agronomy. We analyze the development of this approach applied to a few examples of natural resources management.
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Dates et versions

hal-00999966 , version 1 (04-06-2014)
hal-00999966 , version 2 (23-05-2016)

Identifiants

  • HAL Id : hal-00999966 , version 1

Citer

Fabien F. Campillo, Rivo R. Rakotozafy, Vivien V. Rossi. Computational probability modeling and Bayesian inference. 2007 International Conference in Honor of Claude Lobry, Sep 2007, Saint-Louis, Senegal. ⟨hal-00999966v1⟩

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