
Experts in Uncertainty
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Content
- Intro
- Contents
- Introduction
- PART I: EXPERTS AND OPINIONS
- 1. Think Tanks and Oracles
- Background
- The RAND Corporation
- Herman Kahn
- Scenario analysis
- The Delphi method
- Conclusions: Toward a methodology for expert opinion
- 2. Expert Opinion in Practice
- The Aerospace sector
- Military intelligence
- Probabilistic risk analysis
- Policy analysis
- 3. Probabilistic Thinking
- Thinking
- Representing uncertainty in artificial intelligence
- Fuzziness
- Conclusion
- 4. Heuristics and Biases
- Availability
- Anchoring
- Representativeness
- Control
- The base rate fallacy
- Overconfidence and calibration
- Conclusion
- 5. Building rational consensus
- Rational consensus
- Principles
- Conclusion
- PART II: SUBJECTIVE PROBABILITY
- 6. Savage's Normative Decision Theory
- The decision model
- The representation theorem
- Observation
- Supplement
- 7. Relative Frequencies and Exchangeability
- The frequentist account of learning by experience
- Expected frequency
- Exchangeability
- De Finetti's finite representation theorem
- Supplement
- 8. Elicitation and Scoring
- Elicitation
- Scoring
- Methodological problems
- Practical guidelines
- 9. Scoring Rules for Evaluating and Weighing Assessments
- Improper scoring rules
- Scoring rules for individual variables
- Proper scoring rules for average probabilities
- Asymptotic properties
- A menu of weights
- Heuristics of weighing
- Supplement
- 10. Two Experiments with Calibration and Entropy
- Calibration and knowledge
- brief review of the literature
- The mechanical engineer experiment
- The managers experiment
- Conclusion
- PART III: COMBINING EXPERT OPINIONS
- 11. Combining Expert Opinions
- Review of the Literature
- Weighted combinations of probabilities
- Bayesian combinations
- Psychological scaling
- Conclusion
- 12. The Classical Model
- Notation and definitions
- Basic model
- uncertain events
- Basic model
- continuous variables
- Variations and enhancements
- Issues
- Measuring and optimizing performance
- virtual weights
- Correlation
- Conclusions
- 13. The Bayesian Model
- Basic theory
- Notations and definitions
- The Mendel-Sheridan model
- assumptions
- Evaluation of model performance via bilinear loss functions
- A partially exchangeable Bayesian model
- Conclusions
- 14. Psychological Scaling Models: Paired Comparisons
- Generic issues
- Significant preference for one expert
- Significant preference for the set of experts
- The Thurstone model
- The Bradley-Terry model
- The negative exponential lifetime model
- Relation to principles for expert opinion in science
- 15. Applications
- Applications of the classical model
- The Royal Dutch Meteorological study
- Bayesian analysis
- Flange connections at a process plant-paired comparisons
- Flange connections at a process plant-the classical model
- Supplement
- 16. Conclusions
- Part I
- Part II
- Part III
- Appendix A. Mathematical Framework and Interpretation
- Mathematical framework
- Interpretation
- Conditional probability, independence, Bayes' theorem
- Expectation, moments, moment convergence
- Distributions
- Entropy, information, relative information
- Appendix B. Standard normal, inverse normal, Chi square, coefficient of agreement, coefficient of concordance
- References
- Author Index
- A
- B
- C
- D
- E
- F
- G
- H
- J
- K
- L
- M
- O
- P
- R
- S
- T
- V
- W
- Z
- Subject Index
- A
- B
- C
- D
- E
- F
- H
- I
- J
- K
- L
- M
- N
- O
- P
- Q
- R
- S
- T
- U
- V
- W
- Z
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