IDEAS home Printed from https://ideas.repec.org/a/eee/reensy/v95y2010i4p354-360.html
   My bibliography  Save this article

An effective algorithm for computing global sensitivity indices (EASI)

Author

Listed:
  • Plischke, Elmar

Abstract

We present an algorithm named EASI that estimates first order sensitivity indices from given data using Fast Fourier Transformations. Hence it can be used as a post-processing module for pre-computed model evaluations. Ideas for the estimation of higher order sensitivity indices are also discussed.

Suggested Citation

  • Plischke, Elmar, 2010. "An effective algorithm for computing global sensitivity indices (EASI)," Reliability Engineering and System Safety, Elsevier, vol. 95(4), pages 354-360.
    • Handle: RePEc:eee:reensy:v:95:y:2010:i:4:p:354-360
    DOI: 10.1016/j.ress.2009.11.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0951832009002579
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.ress.2009.11.005?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. Saltelli A. & Tarantola S., 2002. "On the Relative Importance of Input Factors in Mathematical Models: Safety Assessment for Nuclear Waste Disposal," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 702-709, September.
    2. Sobol’, I.M. & Tarantola, S. & Gatelli, D. & Kucherenko, S.S. & Mauntz, W., 2007. "Estimating the approximation error when fixing unessential factors in global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 92(7), pages 957-960.
    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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Lo Piano, Samuele & Ferretti, Federico & Puy, Arnald & Albrecht, Daniel & Saltelli, Andrea, 2021. "Variance-based sensitivity analysis: The quest for better estimators and designs between explorativity and economy," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    2. 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).
    3. Tissot, Jean-Yves & Prieur, Clémentine, 2012. "Bias correction for the estimation of sensitivity indices based on random balance designs," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 205-213.
    4. Nađa Džubur & David Laner, 2018. "Evaluation of Modeling Approaches to Determine End‐of‐Life Flows Associated with Buildings: A Viennese Case Study on Wood and Contaminants," Journal of Industrial Ecology, Yale University, vol. 22(5), pages 1156-1169, October.
    5. Paredes-Gazquez, Juan Diego & Rodriguez-Fernandez, José Miguel & de la Cuesta-Gonzalez, Marta, 2016. "Measuring corporate social responsibility using composite indices: Mission impossible? The case of the electricity utility industry," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 19(1), pages 142-153.
    6. Plischke, Elmar, 2012. "An adaptive correlation ratio method using the cumulative sum of the reordered output," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 149-156.
    7. Manel Baucells & Emanuele Borgonovo, 2013. "Invariant Probabilistic Sensitivity Analysis," Management Science, INFORMS, vol. 59(11), pages 2536-2549, November.
    8. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    9. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.
    10. Paolo Paruolo & Michaela Saisana & Andrea Saltelli, 2013. "Ratings and rankings: voodoo or science?," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 176(3), pages 609-634, June.
    11. Spiessl, Sabine M. & Kucherenko, Sergei & Becker, Dirk-A. & Zaccheus, Oluyemi, 2019. "Higher-order sensitivity analysis of a final repository model with discontinuous behaviour using the RS-HDMR meta-modeling approach," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 149-158.
    12. Spiessl, Sabine M. & Becker, Dirk-A., 2015. "Sensitivity analysis of a final repository model with quasi-discrete behaviour using quasi-random sampling and a metamodel approach in comparison to other variance-based techniques," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 287-296.
    13. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
    14. Goda, Takashi, 2021. "A simple algorithm for global sensitivity analysis with Shapley effects," Reliability Engineering and System Safety, Elsevier, vol. 213(C).
    15. 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.
    16. 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).

    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. Mara, Thierry Alex, 2009. "Extension of the RBD-FAST method to the computation of global sensitivity indices," Reliability Engineering and System Safety, Elsevier, vol. 94(8), pages 1274-1281.
    2. Mirko Ginocchi & Ferdinanda Ponci & Antonello Monti, 2021. "Sensitivity Analysis and Power Systems: Can We Bridge the Gap? A Review and a Guide to Getting Started," Energies, MDPI, vol. 14(24), pages 1-59, December.
    3. Borgonovo, E., 2010. "Sensitivity analysis with finite changes: An application to modified EOQ models," European Journal of Operational Research, Elsevier, vol. 200(1), pages 127-138, January.
    4. 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.
    5. 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.
    6. 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.
    7. 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.
    8. 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.
    9. Borgonovo, Emanuele & Plischke, Elmar, 2016. "Sensitivity analysis: A review of recent advances," European Journal of Operational Research, Elsevier, vol. 248(3), pages 869-887.
    10. 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.
    11. Rahman, Sharif, 2011. "Global sensitivity analysis by polynomial dimensional decomposition," Reliability Engineering and System Safety, Elsevier, vol. 96(7), pages 825-837.
    12. 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).
    13. Xu, Chonggang & Gertner, George Zdzislaw, 2008. "A general first-order global sensitivity analysis method," Reliability Engineering and System Safety, Elsevier, vol. 93(7), pages 1060-1071.
    14. Plischke, Elmar & Borgonovo, Emanuele & Smith, Curtis L., 2013. "Global sensitivity measures from given data," European Journal of Operational Research, Elsevier, vol. 226(3), pages 536-550.
    15. Hu, Zhen & Mahadevan, Sankaran, 2019. "Probability models for data-Driven global sensitivity analysis," Reliability Engineering and System Safety, Elsevier, vol. 187(C), pages 40-57.
    16. Beccacece, F. & Borgonovo, E., 2011. "Functional ANOVA, ultramodularity and monotonicity: Applications in multiattribute utility theory," European Journal of Operational Research, Elsevier, vol. 210(2), pages 326-335, April.
    17. Xu, Chonggang & Gertner, George, 2011. "Understanding and comparisons of different sampling approaches for the Fourier Amplitudes Sensitivity Test (FAST)," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 184-198, January.
    18. Lo Piano, Samuele & Ferretti, Federico & Puy, Arnald & Albrecht, Daniel & Saltelli, Andrea, 2021. "Variance-based sensitivity analysis: The quest for better estimators and designs between explorativity and economy," Reliability Engineering and System Safety, Elsevier, vol. 206(C).
    19. Emanuele Borgonovo, 2010. "A Methodology for Determining Interactions in Probabilistic Safety Assessment Models by Varying One Parameter at a Time," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 385-399, March.
    20. Allaire, Douglas L. & Willcox, Karen E., 2012. "A variance-based sensitivity index function for factor prioritization," Reliability Engineering and System Safety, Elsevier, vol. 107(C), pages 107-114.

    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:eee:reensy:v:95:y:2010:i:4:p:354-360. 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: Catherine Liu (email available below). General contact details of provider: https://www.journals.elsevier.com/reliability-engineering-and-system-safety .

    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.