IDEAS home Printed from https://ideas.repec.org/a/wly/riskan/v16y1996i4p587-598.html
   My bibliography  Save this article

Variance‐Based Importance Analysis Applied to a Complex Probabilistic Performance Assessment

Author

Listed:
  • Randall D. Manteufel

Abstract

The most important input parameters in a complex probabilistic performance assessment are identified using a variance‐based method and compared with those identified using a regression‐based method. The variance‐based method has the advantage of not requiring assumptions about the functional relationship between input and output parameters. However, it has the drawback of requiring heuristic assessments of threshold variance ratios above which a parameter is considered important, and it also requires numerous executions of the computer program, which may be computationally expensive. Both methods identified the same top 5 and 7 of the top 10 most important parameters for a system having 195 inputs. Although no distinct advantage for the variance‐based approach was identified, the ideas which motivate the new approach are sound and suggest new avenues for exploring the relationships between the inputs and the output of a complex system.

Suggested Citation

  • Randall D. Manteufel, 1996. "Variance‐Based Importance Analysis Applied to a Complex Probabilistic Performance Assessment," Risk Analysis, John Wiley & Sons, vol. 16(4), pages 587-598, August.
    • Handle: RePEc:wly:riskan:v:16:y:1996:i:4:p:587-598
    DOI: 10.1111/j.1539-6924.1996.tb01104.x
    as

    Download full text from publisher

    File URL: https://doi.org/10.1111/j.1539-6924.1996.tb01104.x
    Download Restriction: no
    File URL: https://libkey.io/10.1111/j.1539-6924.1996.tb01104.x?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
    ---><---

    References listed on IDEAS

    as
    1. Ronald L. Iman & Jon C. Helton, 1991. "The Repeatability of Uncertainty and Sensitivity Analyses for Complex Probabilistic Risk Assessments," Risk Analysis, John Wiley & Sons, vol. 11(4), pages 591-606, December.
    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. William B. Mills & Christine S. Lew & Cheng Y. Hung, 1999. "Sensitivity of Concentration and Risk Predictions in the PRESTO and MMSOILS Multimedia Models: Regression Technique Assessment," Risk Analysis, John Wiley & Sons, vol. 19(3), pages 511-525, June.

    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. S. Cucurachi & E. Borgonovo & R. Heijungs, 2016. "A Protocol for the Global Sensitivity Analysis of Impact Assessment Models in Life Cycle Assessment," Risk Analysis, John Wiley & Sons, vol. 36(2), pages 357-377, February.
    2. Douglas L. Van Bossuyt & Bryan M. O'Halloran & Ryan M. Arlitt, 2019. "A method of identifying and analyzing irrational system behavior in a system of systems," Systems Engineering, John Wiley & Sons, vol. 22(6), pages 519-537, November.
    3. Bui, Ha & Sakurahara, Tatsuya & Pence, Justin & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "An algorithm for enhancing spatiotemporal resolution of probabilistic risk assessment to address emergent safety concerns in nuclear power plants," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 405-428.
    4. Sakurahara, Tatsuya & Schumock, Grant & Reihani, Seyed & Kee, Ernie & Mohaghegh, Zahra, 2019. "Simulation-Informed Probabilistic Methodology for Common Cause Failure Analysis," Reliability Engineering and System Safety, Elsevier, vol. 185(C), pages 84-99.
    5. Takeda, Satoshi & Kitada, Takanori, 2021. "Simple method based on sensitivity coefficient for stochastic uncertainty analysis in probabilistic risk assessment," Reliability Engineering and System Safety, Elsevier, vol. 209(C).
    6. Jon C. Helton, 1994. "Treatment of Uncertainty in Performance Assessments for Complex Systems," Risk Analysis, John Wiley & Sons, vol. 14(4), pages 483-511, August.
    7. J. C. Helton & D. R. Anderson & H.‐N. Jow & M. G. Marietta & G. Basabilvazo, 1999. "Performance Assessment in Support of the 1996 Compliance Certification Application for the Waste Isolation Pilot Plant," Risk Analysis, John Wiley & Sons, vol. 19(5), pages 959-986, October.
    8. Tatsuya Sakurahara & Seyed Reihani & Ernie Kee & Zahra Mohaghegh, 2020. "Global importance measure methodology for integrated probabilistic risk assessment," Journal of Risk and Reliability, , vol. 234(2), pages 377-396, April.

    More about this item

    Statistics

    Access and download statistics

    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:wly:riskan:v:16:y:1996:i:4:p:587-598. 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: Wiley Content Delivery (email available below). General contact details of provider: https://doi.org/10.1111/(ISSN)1539-6924 .

    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.