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Bayesian Categorical Data Analysis

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

Abstract

Some interesting research challenges for Bayesian inference arise from binary and categorical data, including more traditional inference problems like contingency tables with sparse data and case-control studies as well as more recent research frontiers like non-standard link function for binary data regression.

Keywords

Monte Carlo Marginal Likelihood Deviance Information Criterion Markov Chain Monte Carlo Sampling High Posterior Density 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer New York 2010

Authors and Affiliations

  • Ming-Hui Chen
    • 1
  • Dipak K. Dey
    • 1
  • Peter Müller
    • 2
  • Dongchu Sun
    • 3
  • Keying Ye
    • 4
  1. 1.Department of StatisticsUniversity of ConnecticutStorrsUSA
  2. 2.Department of BiostatisticsThe University of Texas, M. D. Anderson Cancer CenterHoustonUSA
  3. 3.Department of StatisticsUniversity of Missouri-ColumbiaColumbiaUSA
  4. 4.Department of Management Science and Statistics, College of BusinessUniversity of Texas at San AntonioSan AntonioUSA

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