Derivative-Based Global Sensitivity Measures and Their Link with Sobol' Sensitivity Indices

被引:25
作者
Kucherenko, Sergei [1 ]
Song, Shugfang [1 ]
机构
[1] Imperial Coll London, London SW7 2AZ, England
来源
MONTE CARLO AND QUASI-MONTE CARLO METHODS | 2016年 / 163卷
关键词
Global sensitivity analysis; Monte Carlo methods; Quasi Monte Carlo methods; Derivative based global measures; Morris method; Sobol' sensitivity indices; SYSTEMS;
D O I
10.1007/978-3-319-33507-0_23
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
The variance-based method of Sobol' sensitivity indices is very popular among practitioners due to its efficiency and easiness of interpretation. However, for high-dimensional models the direct application of this method can be very time-consuming and prohibitively expensive to use. One of the alternative global sensitivity analysis methods known as the method of derivative based global sensitivity measures (DGSM) has recently become popular among practitioners. It has a link with the Morris screening method and Sobol' sensitivity indices. DGSM are very easy to implement and evaluate numerically. The computational time required for numerical evaluation of DGSM is generally much lower than that for estimation of Sobol' sensitivity indices. We present a survey of recent advances in DGSM and new results concerning new lower and upper bounds on the values of Sobol' total sensitivity indices S-i(tot). Using these bounds it is possible in most cases to get a good practical estimation of the values of S-i(tot). Several examples are used to illustrate an application of DGSM.
引用
收藏
页码:455 / 469
页数:15
相关论文
共 16 条
  • [1] [Anonymous], 2008, GLOBAL SENSITIVITY A
  • [2] [Anonymous], 2008, EVALUATING DERIVATIV
  • [3] [Anonymous], 2005, REV WILMOTT MAG
  • [4] Importance measures in global sensitivity analysis of nonlinear models
    Homma, T
    Saltelli, A
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 1996, 52 (01) : 1 - 17
  • [5] Quasi-Monte Carlo methods for lattice systems: A first look
    Jansen, K.
    Leovey, H.
    Ammon, A.
    Griewank, A.
    Mueller-Preussker, M.
    [J]. COMPUTER PHYSICS COMMUNICATIONS, 2014, 185 (03) : 948 - 959
  • [6] Global Sensitivity Analysis Challenges in Biological Systems Modeling
    Kiparissides, A.
    Kucherenko, S. S.
    Mantalaris, A.
    Pistikopoulos, E. N.
    [J]. INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH, 2009, 48 (15) : 7168 - 7180
  • [7] Monte Carlo evaluation of derivative-based global sensitivity measures
    Kucherenko, S.
    Rodriguez-Fernandez, M.
    Pantelides, C.
    Shah, N.
    [J]. RELIABILITY ENGINEERING & SYSTEM SAFETY, 2009, 94 (07) : 1135 - 1148
  • [8] Derivative-based global sensitivity measures: General links with Sobol' indices and numerical tests
    Lamboni, M.
    Iooss, B.
    Popelin, A. -L.
    Gamboa, F.
    [J]. MATHEMATICS AND COMPUTERS IN SIMULATION, 2013, 87 : 45 - 54
  • [9] Littlewood J.E., 1973, INEQUALITIES
  • [10] FACTORIAL SAMPLING PLANS FOR PRELIMINARY COMPUTATIONAL EXPERIMENTS
    MORRIS, MD
    [J]. TECHNOMETRICS, 1991, 33 (02) : 161 - 174