This paperback edition of a proven classic and the latest edition to the prestigious Wiley Classics Library provides a thorough discussion in the theory and methodology of optimal statistical decisions. While the content does not include the computational advances that have become so popular and well used today, neither does it neglect what purposes are served by those computations. Of particular note is the fact that Bayesian and sequential decision problems are explained from the bottom-up with great care and clarity.
This paperback edition of a proven classic and the latest edition to the prestigious Wiley Classics Library provides a thorough discussion in the theory and methodology of optimal statistical decisions. While the content does not include the computational advances that have become so popular and well used today, neither does it neglect what purposes are served by those computations. Of particular note is the fact that Bayesian and sequential decision problems are explained from the bottom-up with great care and clarity.
Morris DeGroot (now deceased) was a great statistician and gentleman of the 20th Century. Says friend and coworker Joseph B. ("Jay") Kadane of DeGroot in the Foreword, "He was an institutional builder, as founder of the Statistics Department at Carnegie Mellon University and as first Executive Editor of Statistical Science. He was a wonderful colleague and friend, always ready for a chat about principles, a research problem, a departmental problem, a reference, or personal advice."
Inhaltsangabe
Foreword. Preface. PART ONE. SURVEY OF PROBABILITY THEORY. Chapter 1. Introduction. Chapter 2. Experiments, Sample Spaces, and Probability. Chapter 3. Random Variables, Random Vectors, and Distributions Functions. Chapter 4. Some Special Univariate Distributions. Chapter 5. Some Special Multivariate Distributions. PART TWO. SUBJECTIVE PROBABILITY AND UTILITY. Chapter 6. Subjective Probability. Chapter 7. Utility. PART THREE. STATISTICAL DECISION PROBLEMS. Chapter 8. Decision Problems. Chapter 9. Conjugate Prior Distributions. Chapter 10. Limiting Posterior Distributions. Chapter 11. Estimation, Testing Hypotheses, and linear Statistical Models. PART FOUR. SEQUENTIAL DECISIONS. Chapter 12. Sequential Sampling. Chapter 13. Optimal Stopping. Chapter 14. Sequential Choice of Experiments. References. Supplementary Bibliography. Name Index. Subject Index.
