Statistical decision theory and related topics II : proceedings of a symposium held at Purdue University, May 17-19, 1976 /

Statistical Decision Theory and Related Topics.

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: Purdue University
Otros Autores: Gupta, Shanti Swarup, 1925-, Moore, David S.
Formato: Electrónico eBook
Idioma:Inglés
Publicado: New York : Academic Press, �1977.
Temas:
Statistical decision > Congresses.
Prise de d�ecision (Statistique) > Congr�es.
MATHEMATICS > Applied.
MATHEMATICS > Probability & Statistics > General.
Statistical decision
Congress
proceedings (reports)
Conference papers and proceedings
Conference papers and proceedings.
Actes de congr�es.
Acceso en línea:Texto completo
Tabla de Contenidos:
  • Front Cover; Statistical Decision Theory and Related Topics II; Copyright Page; Table of Contents; CONTRIBUTORS TO THE SYMPOSIUM; PREFACE; CHAPTER 1. SELECTING THE LARGEST INTERACTION IN A TWO-FACTOR EXPERIMENT; 1. Introduction; 2. Model and Statistical as sumptions; 4. Selection procedure, and the choice of sample size; 5. Expression for the PCS; 6. LF-configuration of the yij for the 2xc case; 7. Directions of future research; 8. Acknowledgment; References; CHAPTER 2. IMPROVED MINIMAX ESTIMATORS OF NORMAL MEAN VECTORS FOR CERTAIN TYPES OF COVARIANCE MATRICES; 1. Introduction.
  • 2. Basic results3. Applications; References; CHAPTER 3. ON SELECTING A SET OF GOOD POPULATIONS; 1. Introduction; 2. Notation and statement of the problem; 3. The optimal invariant procedure; 4. The number of populations is large; 5. Unknown Bayes, empirical Bayes and compound theory; Appendix; References; CHAPTER 4. CLOSURE THEOREMS FOR SEQUENTIAL-DESIGN PROCESSES; 1. Introduction; 2. Description of the process; 3. Basic theorems for a compact action space; 4. Basic theorems for general actions spaces; 5. Bayes procedures; 6. Available actions dependent on past observations.
  • 7. Dynamic programmingReferences; CHAPTER 5. A SUBSET SELECTION PROBLEM EMPLOYING A NEW CRITERION; 1. Introduction and summary; 2. Loss function; 3. Normal model; 4. Computations; 5. Comparison of stategies; 6. Estimates based on Monte Carlo Calculations; 7. Polemics; APPENDIX; References; CHAPTER 6. EXAMPLES RELEVANT TO THE ROBUSTNESS OF APPLIED INFERENCES; 1. Introdcution; 2. Bayesian robustness; 3. Examples; 4. Concluding remark; References; CHAPTER 7. ON SOME r-MINIMAX SELECTION AND MULTIPLE COMPARISON PROCEDURES; 1. Introduction; 2. Selection procedures for the ""best"" populations.
  • ReferencesCHAPTER 8. MORE ON INCOMPLETE AND BOUNDEDLY COMPLETE FAMILIES OF DISTRIBUTIONS; 1. Introduction; 2. Distributions symmetric about; 3. Two-sample families; 4. Families restricted by a nonlinear condition; References; CHAPTER 9. ROBUST COVARIANCES; 1. Introduction; 2. Maximum likelihood estimates; 3. Estimates determined by implicit equations; 4. Breakdown properties; 5. A note on computation; 6. Large samples properties; 7. Least informative distributions: location; 8. Least informative distributions: covariance; 9. Spherical symmetry? A note on models; Appendix; Acknowledgement.
  • ReferencesCHAPTER 10. ASYMPTOTICALLY MINIMAX ESTIMATION OF CONCAVE AND CONVEX DISTRIBUTION FUNCTIONS. II; 0. Introduction; 5. Estimating concave F under conditions (5.3) ; CHAPTER 11. SEQUENTIAL DECISION ABOUT A NORMAL MEAN; 1. Introduction; 2. Probability of error; 3. Expected sample size; References; CHAPTER 12.A REDUCTION THEOREM FOR CERTAIN SEQUENTIAL EXPERIMENTS; 1. Introduction; 2. Notation and main assumptions; 3. A reduction procedure; 4. Independent observations; 5. Some applications to tests and estimates; References; CHAPTER 13. ROBUST DESIGNS FOR REGRESSION PROBLEMS.

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