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Introduction to statistical decision theory /

by Pratt, John W. (John Winsor); Raiffa, Howard; Schlaifer, Robert.
Material type: materialTypeLabelBookPublisher: Cambridge, Mass. : MIT Press, c1995Description: xix, 875 p. : ill. ; 26 cm.ISBN: 0262161443 (cloth); 9780262662062 (pbk).Subject(s): Statistical decision
Contents:
1. Introduction -- 2. An Informal Treatment of Foundations -- 3. A Formal Treatment of Foundations -- 4. Assessment of Utilities for Consequences -- 5. Quantification of Judgments -- 6. Analysis of Decision Trees -- 7. Random Variables -- 8. Continuous Lotteries and Expectations -- 9. Special Univariate Distributions -- 10. Conditional Probability and Bayes' Theorem -- 11. Bernoulli Process -- 12. Terminal Analysis: Opportunity Loss and the Value of Perfect Information -- 13. Paired Random Variables -- 14. Preposterior Analysis: The Value of Sample Information -- 15. Poisson Process -- 16. Normal Process with Known Variance -- 17. Normal Process with Unknown Variance -- 18. Large Sample Theory -- 19. Statistical Analysis in Normal Form -- 20. Classical Methods -- 21. Multivariate Random Variables -- 22. The Multivariate Normal Distribution -- 23A. Choosing the Best of Several Processes -- 23B. Allowance for Uncertain Bias -- 23C. Stratification -- 23D. The Portfolio Problem.
24. Normal Linear Regression with Known Variance -- Appendix 1: The Terminology of Sets -- Appendix 2: Elements of Matrix Theory -- Appendix 3: Properties of Utility Functions for Monetary Consequences.
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Includes bibliographical references (p. [861]-864) and index.

1. Introduction -- 2. An Informal Treatment of Foundations -- 3. A Formal Treatment of Foundations -- 4. Assessment of Utilities for Consequences -- 5. Quantification of Judgments -- 6. Analysis of Decision Trees -- 7. Random Variables -- 8. Continuous Lotteries and Expectations -- 9. Special Univariate Distributions -- 10. Conditional Probability and Bayes' Theorem -- 11. Bernoulli Process -- 12. Terminal Analysis: Opportunity Loss and the Value of Perfect Information -- 13. Paired Random Variables -- 14. Preposterior Analysis: The Value of Sample Information -- 15. Poisson Process -- 16. Normal Process with Known Variance -- 17. Normal Process with Unknown Variance -- 18. Large Sample Theory -- 19. Statistical Analysis in Normal Form -- 20. Classical Methods -- 21. Multivariate Random Variables -- 22. The Multivariate Normal Distribution -- 23A. Choosing the Best of Several Processes -- 23B. Allowance for Uncertain Bias -- 23C. Stratification -- 23D. The Portfolio Problem.

24. Normal Linear Regression with Known Variance -- Appendix 1: The Terminology of Sets -- Appendix 2: Elements of Matrix Theory -- Appendix 3: Properties of Utility Functions for Monetary Consequences.

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