Methodology for quantifying uncertainty in models.

摘要

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.