Publication from the frontier

In conjunction with the conference in San Antonio last March, I have received the book Frontiers of Statistical Decision Making and Bayesian Analysis: In Honor of James O. Berger edited by Ming-Hui Chen (University of Connecticut), Dipak K. Dey (University of Connecticut), Peter Müller (University of Texas M. D. Anderson Cancer Center), Dongchu Sun (University of Missouri- Columbia) and Keying Ye (University of Texas at San Antonio), who, incidentally, were are PhD students of Jim Berger at the time I visited Purdue University. The book has been edited in depth and so it reads very well, with contributions regrouped by chapters. Here is the table of contents:

  1. Introduction.
  2. Objective Bayesian inference with applications.
  3. Bayesian decision based estimation and predictive inference.
  4. Bayesian model selection and hypothesis tests.
  5. Bayesian computer models.
  6. Bayesian nonparametrics and semi-parametrics.
  7. Bayesian case influence and frequentist interface.
  8. Bayesian clinical trials.
  9. Bayesian methods for genomics, molecular, and systems biology.
  10. Bayesian data mining and machine learning.
  11. Bayesian inference in political and social sciences, finance, and marketing.
  12. Bayesian categorical data analysis.
  13. Bayesian geophysical, spatial, and temporal statistics.
  14. Posterior simulation and Monte Carlo methods.

whose final chapter (the only one missing Bayesian from the title!) contains our contribution with Jean-Michel Marin.

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