A methodology for quantifying uncertainty in models
Conference
·
OSTI ID:10185532
This paper, condensed from McKay et al. (1992) outlines an analysis of uncertainty in the output of computer models arising from uncertainty in inputs (parameters). Uncertainty of this type most often arises when proper input values are imprecisely known. Uncertainty in the output is quantified in its probability distribution, which results from treating the inputs as random variables. The assessment of which inputs are important (sensitivity analysis) with respect to uncertainty is done relative to the probability distribution of the output.
- Research Organization:
- Los Alamos National Lab., NM (United States)
- Sponsoring Organization:
- Nuclear Regulatory Commission, Washington, DC (United States)
- DOE Contract Number:
- W-7405-ENG-36
- OSTI ID:
- 10185532
- Report Number(s):
- LA-UR--93-3160; CONF-9309215--1; ON: DE93040154
- Country of Publication:
- United States
- Language:
- English
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