Empirical Bayes and Likelihood Inference

1. Front Matter

   Pages i-xiv

   PDF

2. Bayes/EB Ranking, Histogram and Parameter Estimation: Issues and Research Agenda

   • T. A. Louis

   Pages 1-16

3. Empirical Bayes Estimators and EM Algorithms in One-Way Analysis of Variance Situations

   • I. Guttman

   Pages 17-32

4. EB and EBLUP in Small Area Estimation

   • J. N. K. Rao

   Pages 33-43

5. Semiparametric Empirical Bayes Estimation in Linear Models

   • P. K. Sen

   Pages 45-65

6. Empirical Bayes Procedures for a Change Point Problem with Application to HIV/AIDS Data

   • S.-L. T. Normand, K. Doksum

   Pages 67-79

7. Bayes and Empirical Bayes Estimates of Survival and Hazard Functions of a Class of Distributions

   • M. Ahsanullah, S. E. Ahmed

   Pages 81-87

8. Bayes and Empirical Bayes Procedures for Selecting Good Populations From a Translated Exponential Family

   • R. S. Singh

   Pages 89-101

9. Shrinkage Estimation of Regression Coefficients From Censored Data With Multiple Observations

   • S. E. Ahmed

   Pages 103-120

10. Bayesian and Likelihood Inference for the Generalized Fieller—Creasy Problem

    • M. Yin, M. Ghosh

    Pages 121-139

11. The Estimation of Ratios From Paired Data

    • D. A. Sprott

    Pages 141-159

12. Meta-Analysis: Conceptual Issues of Addressing Apparent Failure of Individual Study Replication or “Inexplicable” Heterogeneity

    • K. O’Rourke

    Pages 161-183

13. Ancillary Information for Statistical Inference

    • D. A. S. Fraser, N. Reid

    Pages 185-209

14. The Relevance Weighted Likelihood With Applications

    • F. Hu, J. V. Zidek

    Pages 211-235

15. Back Matter

    Pages 237-238

    PDF

Bayesian and likelihood approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both approaches emphasize the construction of interval estimates of unknown parameters. Empirical Bayes methods have historically emphasized instead the construction of point estimates. In this volume researchers present recent work on several aspects of Bayesian, likelihood and empirical Bayes methods, presented at a workshop held in Montreal, Canada. The goal of the workshop was to explore the linkages among the methods, and to suggest new directions for research in the theory of inference.

• Estimator
• Likelihood
• Variance
• algorithms
• analysis of variance
• expectation–maximization algorithm

• Department of Mathematics, University of Regina, Regina, Canada

  S. E. Ahmed

• Department of Statistics, University of Toronto, Toronto, Canada

  N. Reid

Policies and ethics