IDEAS home Printed from https://ideas.repec.org/a/spr/stmapp/v24y2015i3p411-426.html
   My bibliography  Save this article

Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix

Author

Listed:
  • Xue-ping Chen
  • Jin-Guan Lin
  • Xiao-di Wang
  • Xing-fang Huang

Abstract

In this paper, the use of orthogonal arrays with strength $$s>p,$$ s > p , where $$p$$ p is the required strength, for global sensitivity analysis is considered. We first generalize the alias matrix for ANOVA high-dimensional model representation based on matrix image, and then by sequentially minimizing the squared alias degrees, we present a approach for the estimation of sensitivity indices. A two-level orthogonal array with 16 runs and a four-level orthogonal array with 64 runs are studied for estimating both low-order and high-order significant sensitivity indices. Moreover, models containing larger than 10 input factors are also investigated. All cases show that designs with smaller squared alias degree have less bias and variance for the estimations of global sensitivity indices. Copyright Springer-Verlag Berlin Heidelberg 2015

Suggested Citation

  • Xue-ping Chen & Jin-Guan Lin & Xiao-di Wang & Xing-fang Huang, 2015. "Further results on orthogonal arrays for the estimation of global sensitivity indices based on alias matrix," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 24(3), pages 411-426, September.
  • Handle: RePEc:spr:stmapp:v:24:y:2015:i:3:p:411-426
    DOI: 10.1007/s10260-014-0290-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10260-014-0290-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10260-014-0290-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Dimov, I. & Georgieva, R., 2010. "Monte Carlo algorithms for evaluating Sobol’ sensitivity indices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(3), pages 506-514.
    2. Pang, Shanqi & Zhang, Yingshan & Liu, Sanyang, 2004. "Further results on the orthogonal arrays obtained by generalized Hadamard product," Statistics & Probability Letters, Elsevier, vol. 68(1), pages 17-25, June.
    3. Tarantola, S. & Gatelli, D. & Mara, T.A., 2006. "Random balance designs for the estimation of first order global sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 91(6), pages 717-727.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Sibdari, Soheil & Mohammadian, Iman & Pyke, David F., 2018. "On the impact of jet fuel cost on airlines’ capacity choice: Evidence from the U.S. domestic markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 111(C), pages 1-17.
    2. Wei, Pengfei & Lu, Zhenzhou & Yuan, Xiukai, 2013. "Monte Carlo simulation for moment-independent sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 110(C), pages 60-67.
    3. Zhai, Qingqing & Yang, Jun & Zhao, Yu, 2014. "Space-partition method for the variance-based sensitivity analysis: Optimal partition scheme and comparative study," Reliability Engineering and System Safety, Elsevier, vol. 131(C), pages 66-82.
    4. Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
    5. Jung, WoongHee & Taflanidis, Alexandros A., 2023. "Efficient global sensitivity analysis for high-dimensional outputs combining data-driven probability models and dimensionality reduction," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    6. Zhang, Xufang & Pandey, Mahesh D., 2014. "An effective approximation for variance-based global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 164-174.
    7. Kucherenko, S. & Song, S., 2017. "Different numerical estimators for main effect global sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 222-238.
    8. Chen, Xin & Molina-Cristóbal, Arturo & Guenov, Marin D. & Riaz, Atif, 2019. "Efficient method for variance-based sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 181(C), pages 97-115.
    9. Mara, Thierry A. & Tarantola, Stefano, 2012. "Variance-based sensitivity indices for models with dependent inputs," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 115-121.
    10. Gatelli, D. & Kucherenko, S. & Ratto, M. & Tarantola, S., 2009. "Calculating first-order sensitivity measures: A benchmark of some recent methodologies," Reliability Engineering and System Safety, Elsevier, vol. 94(7), pages 1212-1219.
    11. Wei, Pengfei & Lu, Zhenzhou & Song, Jingwen, 2015. "Variable importance analysis: A comprehensive review," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 399-432.
    12. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    13. Li, Chenzhao & Mahadevan, Sankaran, 2016. "An efficient modularized sample-based method to estimate the first-order Sobol׳ index," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 110-121.
    14. Wang, Xiaodi & Zhang, Yingshan & Tang, Yincai, 2014. "Feasible criterion for designs based on fixed effect ANOVA model," Statistics & Probability Letters, Elsevier, vol. 87(C), pages 134-142.
    15. Rahman, Sharif, 2011. "Global sensitivity analysis by polynomial dimensional decomposition," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 825-837.
    16. Azzini, Ivano & Rosati, Rossana, 2021. "Sobol’ main effect index: an Innovative Algorithm (IA) using Dynamic Adaptive Variances," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    17. Heredia, María Belén & Prieur, Clémentine & Eckert, Nicolas, 2021. "Nonparametric estimation of aggregated Sobol’ indices: Application to a depth averaged snow avalanche model," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    18. Pengfei Wei & Zhenzhou Lu & Jingwen Song, 2014. "Moment‐Independent Sensitivity Analysis Using Copula," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 210-222, February.
    19. Kieran Alden & Mark Read & Jon Timmis & Paul S Andrews & Henrique Veiga-Fernandes & Mark Coles, 2013. "Spartan: A Comprehensive Tool for Understanding Uncertainty in Simulations of Biological Systems," PLOS Computational Biology, Public Library of Science, vol. 9(2), pages 1-9, February.
    20. Vuillod, Bruno & Montemurro, Marco & Panettieri, Enrico & Hallo, Ludovic, 2023. "A comparison between Sobol’s indices and Shapley’s effect for global sensitivity analysis of systems with independent input variables," Reliability Engineering and System Safety, Elsevier, vol. 234(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:stmapp:v:24:y:2015:i:3:p:411-426. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.