Case Studies in Bayesian Statistics (eBook, PDF)

Volume VI
Redaktion: Gatsonis, Constantine; Verdinelli, Isabella; Pauler, Donna K.; Higdon, David; Gelman, Andrew; Carriquiry, Alicia; Kass, Robert E.

• Format: PDF

Produktbeschreibung

Bayesian approaches to data analysis sometimes offer important advantages over classical methods. This collection of papers from a workshop on Bayesian statistics discuss important research problems and show the advantages of a Bayesian approach.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 376
• Erscheinungstermin: 17. August 2018
• Englisch
• ISBN-13: 9781461220787
• Artikelnr.: 54789820

Autorenporträt

Constantine Gatsonis, Brown University, Providence, RI, USA / Alicia Carriquiry, Iowa State University, Ames, IA, USA / Andrew Gelman, Columbia University, New York, NY, USA / D. Higdon, Duke University, Durham, NC, USA

Inhaltsangabe

Invited Papers: Statistical Models for Biological Sequence Motif Discovery.- Multi-Course Treatment Strategies for Clinical Trials of Rapidly Fatal Diseases.- Recognition of Faces versus Greebles: A Case Study in Model Selection.- Contributed Papers.

Rezensionen

From the reviews:

TECHNOMETRICS

"...well written and can be appreciated by those with little biology background...In general, I found many of the papers collected in this book interesting...readers who are interested in applying Bayesian analysis in real case studies may find this book useful. One might consider using this book as supplementary material in graduate-level seminar courses on Bayesian data analysis."

Journal of the American Statistical Association, June 2004

"The volume as a whole illustrates the range of models that can now be fitted following the Markov chain Monte Carlo revolution, assess the behavior of posterior summaries under model misspecifications."