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<identifier>oai:HAL:hal-00455050v1</identifier>
<datestamp>2018-01-11</datestamp>
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<publisher>HAL CCSD</publisher>
<title lang=en>Dirichlet prior for cascade SDE with Markov regime-switching</title>
<creator>Tossa, Adaté</creator>
<creator>Bernard, Didier</creator>
<creator>Emilion, Richard</creator>
<creator>K. Iyer, Srikanth</creator>
<contributor>CEntre de REcherches en MAthématiques de la DEcision (CEREMADE) ; Université Paris-Dauphine - Centre National de la Recherche Scientifique (CNRS)</contributor>
<contributor>Laboratoire de Physique de l'Atmosphère Tropicale (LPAT) ; Université des Antilles et de la Guyane (UAG)</contributor>
<contributor>Mathématiques - Analyse, Probabilités, Modélisation - Orléans (MAPMO) ; Université d'Orléans (UO) - Centre National de la Recherche Scientifique (CNRS)</contributor>
<description>15 pages</description>
<identifier>hal-00455050</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00455050</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00455050/document</identifier>
<identifier>https://hal.archives-ouvertes.fr/hal-00455050/file/CSDA06_Srik_Hal.pdf</identifier>
<source>https://hal.archives-ouvertes.fr/hal-00455050</source>
<source>15 pages. 2009</source>
<language>en</language>
<subject lang=en>Stochastic differential equation</subject>
<subject lang=en>Cascades</subject>
<subject lang=en>Dirichlet process</subject>
<subject lang=en>Dissipation</subject>
<subject lang=en>Mangrove</subject>
<subject lang=en>Markov regime switching</subject>
<subject lang=en>Random environment</subject>
<subject lang=en>Stochastic differential equation.</subject>
<subject>[MATH.MATH-ST] Mathematics [math]/Statistics [math.ST]</subject>
<subject>[STAT.TH] Statistics [stat]/Statistics Theory [stat.TH]</subject>
<type>info:eu-repo/semantics/preprint</type>
<type>Preprints, Working Papers, ...</type>
<description lang=en>A Stochastic Differential Equation appearing in the statistical theory of turbulence is extended in random environment by assuming that its two parameters are switched by an unobserved continuoustime Markov chain whose states represent the states of the environment. A Dirichlet process is placed as a prior on the space of the sample paths of this chain, leading to a hierarchical Dirichlet model whose estimation is done both on simulated data and on real data of wind speed measured at the entrance of a mangrove ecosystem.</description>
<date>2009-10-25</date>
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