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Overview
Bayesian and such approaches to inference have a number of points of close contact, especially from an asymptotic point of view. Both emphasize the construction of interval estimates of unknown parameters. 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.
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Table of Contents
Bayes/EB Ranking, Histogram and Parameter Estimation: Issues and Research Agenda (Thomas A. Louis).- Empirical Bayes Estimation and EM Algorithm in One-Way Analysis of Variance Situations (Irwin Guttman).- EB and EBLUP in Small Area Estimation (J.N.K. Rao).- Semiparametrics, Nonparametrics and EB Procedures in Linear Models (P.K. Sen).- Empirical Bayes Procedures for a Change Point Problem with Application to HIV/AIDS Data (Sharon-Lise Normand/Kjell Doksum).- Bayes and Empirical Bayes Estimates of Survival and Hazard Functions of a Class of Distributions (M. Ahsanullah/S. Ejaz Ahmed).- Bayes and Empirical Bayes Procedures for Selecting Good Populations from a Translated Exponential Family (Radhey S. Singh).- PTE and JS Type Estimation of Regression Coefficients from Censored Data with Multiple Observation (S. Ejaz Ahmed).- Bayesian and Likelihood Inference for the Generalized Fieller-Creasy Problem (Ming Yin/Malay Ghosh).- The Estimation of Ratio from Paired Data (David A. Sprott).- Meta-Analysis: Conceptual Issues of Addressing Apparent Failure of Individual Study Replication or "Inexplicable" Heterogeneity (Keith O'Rourke).- Ancillary Information for Statistical Inference (D.A.S. Fraser et al.).- The Relevance Weighted Likelihood with Applications.