Bayesian analysis of stochastic process models
Material type:
TextPublication details: Chichester John Wiley 2012Description: xiii, 290 pages : illustrationsISBN: 9780470744536 Subject(s): Bayesian statistical decision theory | Stochastic processes | Probability & Statistics | Bayesian AnalysisDDC classification: 519.542 Summary: "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"--Summary: "A unique book on Bayesian analyses of stochastic process based models"--
| Item type | Current library | Collection | Call number | Status | Date due | Barcode |
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BK
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Kannur University Central Library Stack | Stack | 519.542 INS/B (Browse shelf (Opens below)) | Available | 37220 |
"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"--
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