The DOI matches its Crossref record.
A Robust Measure of Uncertainty Importance for Use in Fault Tree System Analysis
Abstract
The analysis of probabilistic fault trees often involves the investigation of events that contribute both to the frequency of the top event and to the uncertainty in this frequency. This paper provides a discussion of three measures of the contribution of an event to the total uncertainty in the top event. These measures are known as uncertainty importance measures. Two of these measures are new developments. Each of the measures is shown to have unique advantages and disadvantages. The three measures are based on, respectively, the expected reduction in the variance of the top‐event frequency should the uncertainty in an event be resolved, the same measure based on the log frequency, and a measure based on shifts in the quantiles of the distribution of top‐event frequency.
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Citations
Cited by
A Quantitative Model-Independent Method for Global Sensitivity Analysis of Model Output
Saltelli, A., Tarantola, S., & Chan, K. P.-S. (1999) · Technometrics · doi:10.1080/00401706.1999.10485594 · Cited by 2,275
Sensitivity analysis methods in the biomedical sciences
Qian, G., & Mahdi, A. (2020) · Mathematical Biosciences · doi:10.1016/j.mbs.2020.108306 · Cited by 169
Plischke, E., & Borgonovo, E. (2020) · Risk Analysis · doi:10.1111/risa.13571 · Cited by 15
Metadata
- Authors
- Iman, R. L., & Hora, S. C.
- Venue
- Risk Analysis
- Publisher
- Wiley
- Published
- 1990-09
- Volume
- 10
- Issue
- 3
- Pages
- 401-406
- ISSN
- 0272-4332 (ISSN-L)
- 1539-6924
- OpenAlex
- W1998998358
- Cited by
- 264
- References
- 0
- FWCI
- 0.73
- Type
- journal article
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: A Robust Measure of Uncertainty Importance for Use in Fault Tree System Analysis. https://app.cochat.ai/papers/10.1111/j.1539-6924.1990.tb00523.x
- The paper
- Iman, R. L., & Hora, S. C. (1990). A Robust Measure of Uncertainty Importance for Use in Fault Tree System Analysis. Risk Analysis. https://doi.org/10.1111/j.1539-6924.1990.tb00523.x
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
