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A model for dissipation: cascade SDE with Markov regime-switching and Dirichlet prior
Didier Bernard 1, Richard Emilion 2, Srikanth K. Iyer 2, Adaté Tossa 3
(17/06/2008)

Cascade Stochastic Differential Equation (SDE), a continuous time model for energy dissipation in turbulence, is a generalization of the Yaglom discrete cascade model. We extend this SDE to a model in random environment by assuming that its two parameters are switched by a continuous time Markov chain whose states represent the states of the environment. Moreover, a Dirichlet process is placed as a prior on the space of sample paths of this chain. We propose a Bayesian estimation method of this model which is tested both on simulated data and on real data of wind speed measured at the entrance of the mangrove ecosystem in Guadeloupe.
1 :  Laboratoire de physique de l'Atmosphère Tropicale (LPAT)
Université des Antilles et de la Guyane
2 :  Mathématiques - Analyse, Probabilités, Modélisation - Orléans (MAPMO)
Université d'Orléans – CNRS : UMR7349
3 :  CEntre de REcherches en MAthématiques de la DEcision (CEREMADE)
CNRS : UMR7534 – Université Paris IX - Paris Dauphine
Mathématiques/Statistiques

Statistiques/Théorie
Cascade model – Dirichlet process – dissipation – Mangrove – Markov regime switching – random environment – Stochastic Differential equation.
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