Different numerical estimators for main effect global sensitivity indices
Different numerical estimators for main effect global sensitivity indices
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DOI：
10.1016/j.ress.2017.04.003
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发表时间：
2017-09-01
影响因子：
8.1
通讯作者：
Song, S.
中科院分区：
文献类型：
--
作者：
Kucherenko, S.;Song, S.
基于Sobol敏感度指数的基于方差的全局敏感度指数方法因其易于解释而在从业者中非常流行。对于复杂的实际问题，Sobol指数的计算通常需要大量的函数求值才能达到合理的收敛。在一组试验模型上比较了四种不同的直接计算Sobol主效应敏感指数的公式，并给出了分析结果。所考虑的测试函数代表了在实践中发现的各种类型的模型。公式基于使用蒙特卡罗(MC)和准蒙特卡罗(QMC)技术计算的高维积分。还将直接公式与基于所谓的“双循环重新排序”公式的不同方法进行了比较。研究发现，对于具有自变量和因变量的模型，“双环重排序”(DLR)方法都表现出了较好的性能。
The variance-based method of global sensitivity indices based on Sobol' sensitivity indices became very popular among practitioners due to its easiness of interpretation. For complex practical problems computation of Sobol' indices generally requires a large number of function evaluations to achieve reasonable convergence. Four different direct formulas for computing Sobol' main effect sensitivity indices are compared on a set of test models for which there are analytical results. Considered test functions represent various types of models that are found in practice. Formulas are based on high-dimensional integrals which are evaluated using Monte Carlo (MC) and Quasi Monte Carlo (QMC) techniques. Direct formulas are also compared with a different approach based on the so-called "double loop reordering" formula. It is found that the "double loop reordering" (DLR) approach shows a superior performance among all methods both for models with independent and dependent variables.