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- Applied Bayesian Modelling (978-1-119-95151-3) - Einband - fest (Hardcover)
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„I recommend... highly to statisticians, [and] healthresearchers... among others to consider keeping on their bookshelf.“(Journal of Statistical Computation and Simulation, April2005)
„... a great book... fills a critical gap in existingliterature. It is an excellent book for anyone interested inBayesian modeling...“ (Journal of the American StatisticalAssociation, March 2005)
„It is certainly a fine choice as a supporting reference ineither a first or second Bayesian methods course...“(Technometrics, May 2004)
„... has a contemporary feel, with recent developments infinancial time series modelling and epidemiology included...“(Short Book Reviews, Vol 23(3), December 2003)
Applied Bayesian Modelling
von Peter CongdonThe use of Bayesian statistics has grown significantly in recentyears, and will undoubtedly continue to do so. Applied BayesianModelling is the follow-up to the author's best sellingbook, Bayesian Statistical Modelling, and focuses on thepotential applications of Bayesian techniques in a wide range ofimportant topics in the social and health sciences. Theapplications are illustrated through many real-life examples andsoftware implementation in WINBUGS - a popular softwarepackage that offers a simplified and flexible approach tostatistical modelling. The book gives detailed explanations foreach example - explaining fully the choice of model for eachparticular problem. The book
· Provides a broad and comprehensive account of appliedBayesian modelling.
· Describes a variety of model assessment methods and theflexibility of Bayesian prior specifications.
· Covers many application areas, including panel datamodels, structural equation and other multivariate structuremodels, spatial analysis, survival analysis and epidemiology.
· Provides detailed worked examples in WINBUGS toillustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site.
The book provides a good introduction to Bayesian modelling anddata analysis for a wide range of people involved in appliedstatistical analysis, including researchers and students fromstatistics, and the health and social sciences. The wealth ofexamples makes this book an ideal reference for anyone involved instatistical modelling and analysis.
· Provides a broad and comprehensive account of appliedBayesian modelling.
· Describes a variety of model assessment methods and theflexibility of Bayesian prior specifications.
· Covers many application areas, including panel datamodels, structural equation and other multivariate structuremodels, spatial analysis, survival analysis and epidemiology.
· Provides detailed worked examples in WINBUGS toillustrate the practical application of the techniques described. All WINBUGS programs are available from an ftp site.
The book provides a good introduction to Bayesian modelling anddata analysis for a wide range of people involved in appliedstatistical analysis, including researchers and students fromstatistics, and the health and social sciences. The wealth ofexamples makes this book an ideal reference for anyone involved instatistical modelling and analysis.
