期刊
ENVIRONMENTAL MODELLING & SOFTWARE
卷 108, 期 -, 页码 197-207出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.envsoft.2018.07.019
关键词
Global sensitivity analysis; Distribution-based methods; Moment-independent methods; Multi-method GSA
类别
资金
- UK Natural Environment Research Council [NE/J017450/1]
- UK Engineering and Physical Sciences Research Council [EP/R007330/1]
- Royal Society Wolfson Research Merit Award
- EPSRC [EP/R007330/1] Funding Source: UKRI
- NERC [NE/J017450/1] Funding Source: UKRI
In a previous paper we introduced a distribution-based method for Global Sensitivity Analysis (GSA), called PAWN, which uses cumulative distribution functions of model outputs to assess their sensitivity to the model's uncertain input factors. Over the last three years, PAWN has been employed in the environmental modelling field as a useful alternative or complement to more established variance-based methods. However, a major limitation of PAWN up to now was the need for a tailored sampling strategy to approximate the sensitivity indices. Furthermore, this strategy required three tuning parameters whose optimal choice was rather unclear. In this paper, we present an alternative approximation procedure that tackles both issues and makes PAWN applicable to a generic sample of inputs and outputs while requiring only one tuning parameter. The new implementation therefore allows the user to estimate PAWN indices as complementary metrics in multi-method GSA applications without additional computational cost.
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