Derivative based global sensitivity measures and their link with global sensitivity indices
Derivative based global sensitivity measures and their link with global sensitivity indices
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DOI：
10.1016/j.matcom.2009.01.023
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发表时间：
2009-06-01
影响因子：
4.6
通讯作者：
Kucherenko, S.
中科院分区：
文献类型：
--
作者：
Sobol, I. M.;Kucherenko, S.
定义在单位超立方体H-n中的模型函数，勒贝格测度dx = dx（1）. dx（n）的值。如果函数是平方可积的，则全局敏感性指数为单个因子x（i）或此类因子组的影响提供了充分的估计。也可以使用需要较少计算机时间的替代估计器。如果函数f是可微的。依赖于偏导数f/偏导数x（i）的泛函已经被建议作为x（i）的影响的估计量。由Campolongo、Cariboni和Saltelli修改的Morris重要性度量mu* 是函数mu（i）= integral（Hn）vertical bar partial derivative f/partial derivative x（i）vertical bar dx.nu（i）= integral（Hn）（partial derivative f/partial derivative x（i））（2）dx显然，mu（i）
A model function defined in the unit hypercube H-n with Lebesque measure dx = dx(1)...dx(n) is considered. If the function is square integrable, global sensitivity indices provide adequate estimates for the influence of individual factors x(i) or groups of such factors. Alternative estimators that require less computer time can also be used. If the function f is differentiable. functionals depending on partial derivative f/partial derivative x(i) have been suggested as estimators for the influence of x(i). The Morris importance measure modified by Campolongo, Cariboni and Saltelli mu* is an approximation of the functional mu(i) = integral(Hn) vertical bar partial derivative f/partial derivative x(i)vertical bar dx.nu(i) = integral(Hn) (partial derivative f/partial derivative x(i))(2) dxEvidently, mu(i)