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Frontiers of Statistical Decision Making and Bayesian Analysis

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Cover of 'Frontiers of Statistical Decision Making and Bayesian Analysis'

Table of Contents

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    Book Overview
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    Chapter 1 Introduction
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    Chapter 2 Objective Bayesian Inference with Applications
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    Chapter 3 Bayesian Decision Based Estimation and Predictive Inference
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    Chapter 4 Bayesian Model Selection and Hypothesis Tests
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    Chapter 5 Bayesian Inference for Complex Computer Models
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    Chapter 6 Bayesian Nonparametrics and Semi-parametrics
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    Chapter 7 Bayesian Influence and Frequentist Interface
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    Chapter 8 Bayesian Clinical Trials
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    Chapter 9 Bayesian Methods for Genomics, Molecular and Systems Biology
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    Chapter 10 Bayesian Data Mining and Machine Learning
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    Chapter 11 Bayesian Inference in Political Science, Finance, and Marketing Research
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    Chapter 12 Bayesian Categorical Data Analysis
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    Chapter 13 Bayesian Geophysical, Spatial and Temporal Statistics
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    Chapter 14 Posterior Simulation and Monte Carlo Methods
Attention for Chapter 2: Objective Bayesian Inference with Applications
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Chapter title
Objective Bayesian Inference with Applications
Chapter number 2
Book title
Frontiers of Statistical Decision Making and Bayesian Analysis
Published by
Springer, New York, NY, January 2010
DOI 10.1007/978-1-4419-6944-6_2
Book ISBNs
978-1-4419-6943-9, 978-1-4419-6944-6
Authors

Ming-Hui Chen, Dipak K. Dey, Peter Müller, Dongchu Sun, Keying Ye, Chen, Ming-Hui, Dey, Dipak K., Müller, Peter, Sun, Dongchu, Ye, Keying

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 2 100%

Demographic breakdown

Readers by professional status Count As %
Professor 2 100%
Readers by discipline Count As %
Mathematics 1 50%
Computer Science 1 50%

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