Derivative-based global sensitivity measures: General links with Sobol’ indices and numerical tests
نویسندگان
چکیده
منابع مشابه
Derivative-based global sensitivity measures: General links with Sobol' indices and numerical tests
The estimation of variance-based importance measures (called Sobol’ indices) of the input variables of a numerical model can require a large number of model evaluations. It turns to be unacceptable for high-dimensional model involving a large number of input variables (typically more than ten). Recently, Sobol and Kucherenko have proposed the Derivative-based Global Sensitivity Measures (DGSM),...
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A model function f(x1,. . .,xn) defined in the unit hypercube Hn with Lebesque measure dx= dx1. . .dxn is considered. If the unction is square integrable, global sensitivity indices provide adequate estimates for the influence of individual factors xi or roups of such factors. Alternative estimators that require less computer time can also be used. If the function f is differentiable, unctional...
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The method of derivative based global sensitivity measures (DGSM) has recently become popular among practitioners. It has a strong link with the Morris screening method and Sobol’ sensitivity indices and has several advantages over them. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is generally much lower than that fo...
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متن کاملEstimating Sobol sensitivity indices using correlations
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 ...
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ژورنال
عنوان ژورنال: Mathematics and Computers in Simulation
سال: 2013
ISSN: 0378-4754
DOI: 10.1016/j.matcom.2013.02.002