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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...

Ausführliche Beschreibung

Bibliographische Detailangaben
1. Verfasser: Ruggeri, Fabrizio
Weitere Verfasser: Wiper, Michael P., Ríos Insua, David
Format: Printed Book
Veröffentlicht: Chichester John Wiley 2012
Schlagworte:
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100 1 |a Ruggeri, Fabrizio. 
245 1 0 |a Bayesian analysis of stochastic process models  
260 |a Chichester  |b John Wiley  |c 2012 
300 |a xiii, 290 pages :  |b illustrations ; 
520 |a "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"-- 
520 |a "A unique book on Bayesian analyses of stochastic process based models"-- 
650 0 |a Bayesian statistical decision theory 
650 0 |a Stochastic processes 
650 7 |a Probability & Statistics  
650 7 |a Bayesian Analysis 
700 1 |a Wiper, Michael P. 
700 1 |a Ríos Insua, David, 
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