Extremum sensitivity analysis with polynomial Monte Carlo filtering

Chun Yui Wong, Pranay Seshadri and Geoffrey Parks

Reliability Engineering and System Safety, 2021, vol. 212, issue C

Abstract: Global sensitivity analysis is a powerful set of ideas and heuristics for understanding the importance and interplay between uncertain parameters in a computational model. Such a model is characterized by a set of input parameters and an output quantity of interest, where we typically assume that the inputs are independent and their marginal densities are known. If the output quantity is smooth, polynomial chaos can be used to extract Sobol’ indices.

Keywords: Global sensitivity analysis; Polynomial chaos; Ridge approximations; Extremum sensitivity analysis; Analysis of skewness; Monte Carlo filtering (search for similar items in EconPapers)
Date: 2021
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Citations: View citations in EconPapers (1)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:reensy:v:212:y:2021:i:c:s095183202100154x

DOI: 10.1016/j.ress.2021.107609

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