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Robust Bayesian Analysis

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Cover of 'Robust Bayesian Analysis'

Table of Contents

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