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Bayesian Decision Based Estimation and Predictive Inference

In: Frontiers of Statistical Decision Making and Bayesian Analysis

Author

Listed:
  • Ming-Hui Chen

    (University of Connecticut, Department of Statistics)

  • Dipak K. Dey

    (University of Connecticut, Department of Statistics)

  • Peter Müller

    (The University of Texas, M. D. Anderson Cancer Center, Department of Biostatistics)

  • Dongchu Sun

    (University of Missouri-Columbia, Department of Statistics)

  • Keying Ye

    (University of Texas at San Antonio, Department of Management Science and Statistics, College of Business)

Abstract

Shrinkage estimation is a traditional research topic in Bayesian analysis. The three sections in this chapter convincingly argue that this venerable topic remains a current research frontier with many open problems. The chapter starts with a review of the current state of research and concludes with an insightful discussion of a very specific form of shrinkage estimation arising in recent work on inference in gene-environment interaction studies.

Suggested Citation

  • Ming-Hui Chen & Dipak K. Dey & Peter Müller & Dongchu Sun & Keying Ye, 2010. "Bayesian Decision Based Estimation and Predictive Inference," Springer Books, in: Ming-Hui Chen & Peter Müller & Dongchu Sun & Keying Ye & Dipak K. Dey (ed.), Frontiers of Statistical Decision Making and Bayesian Analysis, chapter 0, pages 69-112, Springer.
    • Handle: RePEc:spr:sprchp:978-1-4419-6944-6_3
    DOI: 10.1007/978-1-4419-6944-6_3
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