Sensitivity in risk analyses with uncertain numbers

@inproceedings{Ferson2006SensitivityIR,
  title={Sensitivity in risk analyses with uncertain numbers},
  author={Scott Ferson and Willis Troy},
  year={2006}
}
Sensitivity analysis is a study of how changes in the inputs to a model influence the results of the model. Many techniques have recently been proposed for use when the model is probabilistic. This report considers the related problem of sensitivity analysis when the model includes uncertain numbers that can involve both aleatory and epistemic uncertainty and the method of calculation is Dempster-Shafer evidence theory or probability bounds analysis. Some traditional methods for sensitivity… CONTINUE READING

From This Paper

Figures, tables, and topics from this paper.

Citations

Publications citing this paper.
Showing 1-10 of 21 extracted citations

References

Publications referenced by this paper.
Showing 1-10 of 110 references

Uncertainty-based sensitivity indices for imprecise probability distributions

Rel. Eng. & Sys. Safety • 2006
View 4 Excerpts
Highly Influenced

Probability Theory, edited by L

E. T. Jaynes
Bretthorst. Cambridge University Press. • 2003
View 4 Excerpts
Highly Influenced

Statistical Reasoning with Imprecise Probabilities

P. Walley
Chapman and Hall, London. • 1991
View 5 Excerpts
Highly Influenced

Arithmetic and Other Operations on Dempster-Shafer Structures

International Journal of Man-Machine Studies • 1986
View 17 Excerpts
Highly Influenced

Response surface methodologies for the design of induction machine self-sensing rotor position saliencies

2007 International Conference on Electrical Machines and Systems (ICEMS) • 2007
View 4 Excerpts
Highly Influenced

Illustration of sampling-based methods for uncertainty and sensitivity analysis.

Risk analysis : an official publication of the Society for Risk Analysis • 2002
View 4 Excerpts
Highly Influenced

Sampling-based methods

J. C. Helton, F. J. Davis
Pages 101-153 in Sensitivity Analysis, edited by A. Saltelli, K. Chan, and E.M. Scott, John Wiley, New York. • 2000
View 5 Excerpts
Highly Influenced

Similar Papers

Loading similar papers…