论文标题
蒙特卡洛估计量和总订购索博的指数
Monte Carlo estimators of first-and total-orders Sobol' indices
论文作者
论文摘要
这项研究比较了两种基于抽样的策略的性能，以同时估计基于总差异的敏感性指数（又称SOBOL'指数）。第一个策略是由[8]引入的，是从业者采用的当前方法。第二个是最近才由本文的作者介绍的。他们都依赖于第一和总订购的不同估计量索博的指标。建立了两组估计量的Asymp-Toic正常方差，并在理论上和数字上比较其精度。结果表明，新策略的表现要优于当前的词：全球灵敏度分析，基于方差的灵敏度指数，一阶SOBOL'索引，总订单索伯'索引，蒙特卡洛估计
This study compares the performances of two sampling-based strategies for the simultaneous estimation of the first-and total-orders variance-based sensitivity indices (a.k.a Sobol' indices). The first strategy was introduced by [8] and is the current approach employed by practitioners. The second one was only recently introduced by the authors of the present article. They both rely on different estimators of first-and total-orders Sobol' indices. The asymp-totic normal variances of the two sets of estimators are established and their accuracies are compared theoretically and numerically. The results show that the new strategy outperforms the current one.Keywords: global sensitivity analysis, variance-based sensitivity indices, first-order Sobol' index, total-order Sobol' index, Monte Carlo estimate, asymptotic normality
