By Wendy Plump
Department of Chemistry
Suppose you’re asking a complex question in which a host of factors, or inputs, could contribute to the answer. In such a circumstance, each of the inputs will influence the certainty of your output answer to a varying degree.
These factors could arise in almost any system that defies easy analysis: the impact of design quirks on the safety of nuclear reactors, or the price of gas and its relation to climate policy, even something as prosaic as the factors that influence a healthy lifestyle. But which inputs in such multivariate systems influence the certainty of the outcome, and what is the degree of that influence? In short, can any of this be reliably quantified?
John Barr, a fifth-year graduate student in the Rabitz Lab and an applied mathematician, answers that question in the affirmative in a new paper out this week in The Society of Industrial and Applied Mathematics/American Statistical Association Journal on Uncertainty Quantification (SIAM/ASA JUQ).