Variance Components and Generalized Sobol' Indices

被引:68
|
作者
Owen, Art B. [1 ]
机构
[1] Stanford Univ, Dept Stat, Stanford, CA 94305 USA
来源
基金
美国国家科学基金会;
关键词
computer experiments; variable importance;
D O I
10.1137/120876782
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper introduces generalized Sobol' indices, compares strategies for their estimation, and makes a systematic search for efficient estimators. Of particular interest are contrasts, sums of squares, and indices of bilinear form which allow a reduced number of function evaluations compared to alternatives. The bilinear framework includes some efficient estimators from Saltelli [Comput. Phys. Comm., 145 (2002), pp. 280-297] and Mauntz [Global Sensitivity Analysis of General Nonlinear Systems, Master's thesis, Imperial College, London, 2002] as well as some new estimators for specific variance components and mean dimensions. This paper also provides a bias corrected version of the estimator of Janon et al. [Asymptotic Normality and Efficiency of Two Sobol' Index Estimators, technical report, INRIA, Rocquencourt, France] and extends the bias correction to generalized Sobol' indices. Some numerical comparisons are given.
引用
收藏
页码:19 / 41
页数:23
相关论文
共 50 条
  • [31] Risk of estimators for Sobol' sensitivity indices based on metamodels
    Panin, Ivan
    ELECTRONIC JOURNAL OF STATISTICS, 2021, 15 (01): : 235 - 281
  • [32] SENSITIVITY STUDY WITH SOBOL' INDICES IN PLANAR MULTISTABLE MECHANISMS
    Dold, Edward J.
    Voglewede, Philip A.
    PROCEEDINGS OF ASME 2022 INTERNATIONAL DESIGN ENGINEERING TECHNICAL CONFERENCES AND COMPUTERS AND INFORMATION IN ENGINEERING CONFERENCE, IDETC-CIE2022, VOL 7, 2022,
  • [33] An Unsupervised Capacity Identification Approach Based on Sobol' Indices
    Pelegrina, Guilherme Dean
    Duarte, Leonardo Tomazeli
    Grabisch, Michel
    Travassos Romano, Joao Marcos
    MODELING DECISIONS FOR ARTIFICIAL INTELLIGENCE (MDAI 2020), 2020, 12256 : 66 - 77
  • [34] Estimation of the Sobol indices in a linear functional multidimensional model
    Fort, Jean-Claude
    Klein, Thierry
    Lagnoux, Agnes
    Laurent, Beatrice
    JOURNAL OF STATISTICAL PLANNING AND INFERENCE, 2013, 143 (09) : 1590 - 1605
  • [35] AN APPROXIMATION THEORETIC PERSPECTIVE OF SOBOL' INDICES WITH DEPENDENT VARIABLES
    Hart, J. L.
    Gremaud, P. A.
    INTERNATIONAL JOURNAL FOR UNCERTAINTY QUANTIFICATION, 2018, 8 (06) : 483 - 493
  • [36] Advanced stochastic approaches for Sobol’ sensitivity indices evaluation
    Venelin Todorov
    Ivan Dimov
    Tzvetan Ostromsky
    Stoyan Apostolov
    Rayna Georgieva
    Yuri Dimitrov
    Zahari Zlatev
    Neural Computing and Applications, 2021, 33 : 1999 - 2014
  • [37] Is VARS more intuitive and efficient than Sobol? indices?
    Puy, Arnald
    Lo Piano, Samuele
    Saltelli, Andrea
    ENVIRONMENTAL MODELLING & SOFTWARE, 2021, 137
  • [38] Advanced stochastic approaches for Sobol' sensitivity indices evaluation
    Todorov, Venelin
    Dimov, Ivan
    Ostromsky, Tzvetan
    Apostolov, Stoyan
    Georgieva, Rayna
    Dimitrov, Yuri
    Zlatev, Zahari
    NEURAL COMPUTING & APPLICATIONS, 2021, 33 (06): : 1999 - 2014
  • [39] Monte Carlo algorithms for evaluating Sobol' sensitivity indices
    Dimov, I.
    Georgieva, R.
    MATHEMATICS AND COMPUTERS IN SIMULATION, 2010, 81 (03) : 506 - 514
  • [40] Iterative estimation of Sobol’ indices based on replicated designs
    Laurent Gilquin
    Clémentine Prieur
    Elise Arnaud
    Hervé Monod
    Computational and Applied Mathematics, 2021, 40