Statistical Decision Theory and Related Topics III

Shanti S. Gupta, James O. Berger

• Publisher: Academic Press
• Year: 2014
• Print ISBN:
  9780123075024
• eBook ISBN:
  9781483259550
• Topic: Mathematics
• Subtopic: Applied Mathematics
• Index: Mathematics

Statistical Decision Theory and Related Topics III, Volume 2 is a collection of papers presented at the Third Purdue Symposium on Statistical Decision Theory and Related Topics, held at Purdue University in June 1981. The symposium brought together many prominent leaders and a number of younger researchers in statistical decision theory and related areas. This volume contains the research papers presented at the symposium and includes works on general decision theory, multiple decision theory, optimum experimental design, sequential and adaptive inference, Bayesian analysis, robustness, and large sample theory. These research areas have seen rapid developments since the preceding Purdue Symposium in 1976, developments reflected by the variety and depth of the works in this volume. Statisticians and mathematicians will find the book very insightful.

Table of contents

• Front Cover
• Statistical Decision Theory and Related Topics III
• Copyright Page
• Table of Contents
• CONTRIBUTORS
• PREFACE
• CONTENTS OF VOLUME 1
• CHAPTER 1. SOME LOCALLY OPTIMAL SUBSET SELECTION RULES BASED ON RANKS
• CHAPTER 2. CERTAIN BOUNDS ON THE CLASS OF ADMISSIBLE ESTIMATORS IN CONTINUOUS EXPONENTIAL FAMILIES
• CHAPTER 3. RIDGE TYPE ESTIMATORS OF MULTINOMIAL CELL PROBABILITIES
• CHAPTER 4. ASYMPTOTICALLY OPTIMAL PROCEDURES FOR SEQUENTIAL ADAPTIVE SELECTION OF THE BEST OF SEVERAL NORMAL MEANS
• CHAPTER 5. MODEL ROBUST CONFIDENCE INTERVALS II
• CHAPTER 6. ADAPTIVE DESIGN AND THE MULTIPERIOD CONTROL PROBLEM
• CHAPTER 7. ON THE RISK OF BAYES ESTIMATES
• CHAPTER 8. THE MINIMAL· COMPLETE CLASS OF PROCEDURES FOR COMBINING INDEPENDENT NONCENTRAL F-TESTS
• CHAPTER 9. RIDGE ESTIMATORS AS CONSTRAINED GENERALIZED LEAST SQUARES
• CHAPTER 10. BOUNDS FOR A K-FOLD INTEGRAL FOR LOCATION AND SCALE PARAMETER MODELS WITH APPLICATIONS TO STATISTICAL RANKING AND SELECTION PROBLEMS
• CHAPTER 11. THE ASYMPTOTIC DISTRIBUTION THEORY OF ONE SAMPLE SIGNED RANK STATISTIC
• CHAPTER 12. ANALYSIS OF DIVERSITY: A UNIFIED APPROACH
• CHAPTER 13. ESTIMATING MANY VARIANCES
• CHAPTER 14. ESTIMATING A POSSIBLY RATIONAL MEAN
• CHAPTER 15. ADAPTIVE PROCEDURES FOR A FINITE NUMBER OF PROBABILITY DISTRIBUTION FAMILIES
• CHAPTER 16. IMPROVEMENTS ON LINEAR MINIMAX ESTIMATES
• CHAPTER 17. CONVERGENCE OF DIRICHLET MEASURES AND THE INTERPRETATION OF THEIR PARAMETER
• CHAPTER 18. ADMISSIBILITY AND LOCAL ASYMPTOTIC ADMISSIBILITY OF PROCEDURES WHICH COMBINE ESTIMATION AND MODEL SELECTION
• CHAPTER 19. OPTIMAL DESIGNS FOR WEIGHTED POLYNOMIAL REGRESSION USING CANONICAL MOMENTS
• CHAPTER 20. HIGHER ORDER ASYMPTOTIC EFFICIENCY OF ESTIMATORS IN DECISION PROCEDURES
• CHAPTER 21. DECISION-THEORETIC REGRESSION DIAGNOSTICS
• CHAPTER 22. CONSTRAINED REGULARIZATION FOR ILL POSED LINEAR OPERATOR EQUATIONS, WITH APPLICATIONS IN METEOROLOGY AND MEDICINE
• CHAPTER 23. DATA FUSION
• CHAPTER 24. SEQUENTIAL CONFIDENCE SETS: ESTIMATION-ORIENTED VERSUS TEST-ORIENTED CONSTRUCTION
• CHAPTER 25. INCORPORATING PRIOR INFORMATION IN MINIMAX ESTIMATION OF THE MEAN OF A GAUSSIAN PROCESS
• CHAPTER 26. EMPIRICAL BAYES ESTIMATION OF THE MEAN OF A NORMAL DISTRIBUTION WITH CONVEX LOSS
• CHAPTER 27. OPTIMUM SUBMEASURES WITH APPLICATION TO FINITE POPULATION SAMPLING
• CHAPTER 28. ON MATCHMAKING
• CHAPTER 29. A CLASS OF GENERALIZED BAYES MINIMAX ESTIMATORS