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Estimating Sobol Sensitivity Indices Using Correlations
Citation:
Glen, G. AND K. K. ISAACS. Estimating Sobol Sensitivity Indices Using Correlations. ENVIRONMENTAL MODELLING AND SOFTWARE. Elsevier Science Ltd, New York, NY, 37(November, 2012):157-166, (2012).
Impact/Purpose:
The National Exposure Research Laboratory′s (NERL) Human Exposure and Atmospheric Sciences Division (HEASD) conducts research in support of EPA′s mission to protect human health and the environment. HEASD′s research program supports Goal 1 (Clean Air) and Goal 4 (Healthy People) of EPA′s strategic plan. More specifically, our division conducts research to characterize the movement of pollutants from the source to contact with humans. Our multidisciplinary research program produces Methods, Measurements, and Models to identify relationships between and characterize processes that link source emissions, environmental concentrations, human exposures, and target-tissue dose. The impact of these tools is improved regulatory programs and policies for EPA.
Description:
Sensitivity analysis is a crucial tool in the development and evaluation of complex mathematical models. Sobol's method is a variance-based global sensitivity analysis technique that has been applied to computational models to assess the relative importance of input parameters on the output. This paper introduces new notation that describes the Sobol indices in terms of the Pearson correlation of outputs from pairs of runs, and introduces correction terms to remove some of the spurious correlation. A variety of estimation techniques are compared for accuracy and precision using the G function as a test case.
URLs/Downloads:
Environmental Modelling & Software
Estimating Sobol Sensitivity Indices Using Correlations (PDF, NA pp, 234 KB, about PDF)