Collecting Bayesian material scattered throughout the literature, Current Trends in Bayesian Methodology with Applications examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics.
Each chapter is self-contained and focuses on a Bayesian methodology. It gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples.
This book reflects the diversity of Bayesian analysis, from novel Bayesian methodology, such as nonignorable response and factor analysis, to state-of-the-art applications in economics, astrophysics, biomedicine, oceanography, and other areas. It guides readers in using Bayesian techniques for a range of statistical analyses.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Satyanshu K. Upadhyay is a professor and head of the Department of Statistics at Banaras Hindu University.
Umesh Singh is a professor in the Department of Statistics at Banaras Hindu University.
Dipak K. Dey is a distinguished professor in the Department of Statistics at the University of Connecticut.
Appaia Loganathan is a professor in the Department of Statistics at Manonmaniam Sundaranar University.
Collecting Bayesian material scattered throughout the literature, this volume examines the latest methodological and applied aspects of Bayesian statistics. The book covers biostatistics, econometrics, reliability and risk analysis, spatial statistics, image analysis, shape analysis, Bayesian computation, clustering, uncertainty assessment, high-energy astrophysics, neural networking, fuzzy information, objective Bayesian methodologies, empirical Bayes methods, small area estimation, and many more topics. Each chapter is self-contained, gives an overview of the area, presents theoretical insights, and emphasizes applications through motivating examples.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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