Robust Bayesian Analysis (eBook, PDF)

Redaktion: Rios Insua, David; Ruggeri, Fabrizio

• Format: PDF

Produktbeschreibung

This book surveys recent developments in one of the most active areas of statistics.

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Produktdetails

• Verlag: Springer US
• Seitenzahl: 422
• Erscheinungstermin: 6. Dezember 2012
• Englisch
• ISBN-13: 9781461213062
• Artikelnr.: 44058658

Inhaltsangabe

1 Bayesian Robustness.- 2 Topics on the Foundations of Robust Bayesian Analysis.- 3 Global Bayesian Robustness for Some Classes of Prior Distributions.- 4 Local Robustness in Bayesian Analysis.- 5 Global and Local Robustness Approaches: Uses and Limitations.- 6 On the Use of the Concentration Function in Bayesian Robustness.- 7 Likelihood Robustness.- 8 Ranges of Posterior Expected Losses and ?-Robust Actions.- 9 Computing Efficient Sets in Bayesian Decision Problems.- 10 Stability of Bayes Decisions and Applications.- 11 Robustness Issues in Bayesian Model Selection.- 12 Bayesian Robustness and Bayesian Nonparametrics.- 13 ?-Minimax: A Paradigm for Conservative Robust Bayesians.- 14 Linearization Techniques in Bayesian Robustness.- 15 Methods for Global Prior Robustness under Generalized Moment Conditions.- 16 Efficient MCMC Schemes for Robust Model Extensions Using Encompassing Dirichlet Process Mixture Models.- 17 Sensitivity Analysis in IctNeo.- 18 Sensitivity of Replacement Priorities for Gas Pipeline Maintenance.- 19 Robust Bayesian Analysis in Medical and Epidemiological Settings.- 20 A Robust Version of the Dynamic Linear Model with an Economic Application.- 21 Prior Robustness in Some Common Types of Software Reliability Model.