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Bayesian analysis of stochastic process models

"This book provides analysis of stochastic processes from a Bayesian perspective with coverage of the main classes of stochastic processing, including modeling, computational, inference, prediction, decision-making and important applied models based on stochastic processes. In offers an introdu...

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Détails bibliographiques
Auteur principal: Ruggeri, Fabrizio
Autres auteurs: Wiper, Michael P., Ríos Insua, David
Format: Printed Book
Publié: Chichester John Wiley 2012
Sujets:
Description
Résumé:"This book provides analysis of stochastic processes from a Bayesian perspective with coverage of the main classes of stochastic processing, including modeling, computational, inference, prediction, decision-making and important applied models based on stochastic processes. In offers an introduction of MCMC and other statistical computing machinery that have pushed forward advances in Bayesian methodology. Addressing the growing interest for Bayesian analysis of more complex models, based on stochastic processes, this book aims to unite scattered information into one comprehensive and reliable volume"--
"A unique book on Bayesian analyses of stochastic process based models"--
Description matérielle:xiii, 290 pages : illustrations ;
ISBN:9780470744536