Titlebook: Low-Probability High-Consequence Risk Analysis; Issues, Methods, and Ray A. Waller,Vincent T. Covello Book 1984 Springer Science+Business M

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The Trade-off Between Expected Risk and the Potential for Large Accidentsle at the same time. This is a topic of great concern to the public. Therefore, several authors have proposed safety goals which give different weights to such large consequences. However, it is difficult to decide which rules should be applied, and it is even more difficult to obtain the weighting

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Models for the use of Expert Opinionsated into his body of knowledge and beliefs. This is done coherently using Bayes’ theorem. Two models are proposed based on normal and lognormal likelihood functions, which represent the decision maker’s model of the credibility of the expert estimates. Several commonly used methods, e. g., taking t

Eviction

Bayesian Estimates for the Rate of three Mile Island Type Releasesmation contained in the prior distribution for the rate and experimental information from the operating experience with pressurized water reactors (PWR). Two prior distributions, but the same operating experience — expressed as total reactor years — are used to obtain the posterior distributions for

碌碌之人

An Incentive Approach to Eliciting Probabilitiest’s forecast of earthquakes), and wants the expert’s reward to depend on the accuracy of the predictions. Assume that the expert compares compensation schemes on the basis of the expected utility of the dollar payoffs, and is willing to reveal his utility function for money. A reward is called “prop

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A Kalman Filter Model for Determining Block and Trickle SNM Lossesered: a block loss during a single time period and a cumulative trickle loss over several time periods. The methodology used is based on a compound Kaiman filter model. Numerical examples illustrate our approach.

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