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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
  2. Altmetric Badge
    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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Title
Robust Bayesian Analysis
Published by
Springer New York, December 2012
DOI 10.1007/978-1-4612-1306-2
ISBNs
978-0-387-98866-5, 978-1-4612-1306-2
Editors

Insua, David Ríos, Ruggeri, Fabrizio

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X Demographics

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 6%
Unknown 16 94%

Demographic breakdown

Readers by professional status Count As %
Professor > Associate Professor 3 18%
Student > Ph. D. Student 3 18%
Student > Bachelor 2 12%
Researcher 2 12%
Student > Doctoral Student 1 6%
Other 1 6%
Unknown 5 29%
Readers by discipline Count As %
Engineering 5 29%
Computer Science 2 12%
Agricultural and Biological Sciences 2 12%
Psychology 1 6%
Economics, Econometrics and Finance 1 6%
Other 0 0%
Unknown 6 35%