IDEAS home Printed from https://ideas.repec.org/a/inm/oropre/v49y2001i5p744-758.html

Input Distribution Selection for Simulation Experiments: Accounting for Input Uncertainty

Author

Listed:
  • Stephen E. Chick

    (Department of Industrial and Operations Engineering, The University of Michigan, 1205 Beal Avenue, Ann Arbor, Michigan 48109-2117)

Abstract

A number of authors have identified problematic issues with techniques used in current simulation practice for selecting probability distributions and their parameters for input to stochastic simulations. A major goal of this paper is to address some of those issues by presenting a self-consistent evaluation of the uncertainty about the mean value of the simulation output, when there is uncertainty in both the parameters and functional form of input distributions (structural uncertainty), and uncertainty due to the stochastic nature of simulation output (stochastic uncertainty), as is common in simulation practice. The analysis leads to an algorithm for randomly sampling input distributions and parameters before each simulation replication, using a Bayesian posterior distribution for input distributions and parameters, given historical data. Mechanisms for addressing issues of importance to the discrete-event simulation community are illustrated by example, such as the specification of prior distributions, and analysis for shifted distributions.

Suggested Citation

  • Stephen E. Chick, 2001. "Input Distribution Selection for Simulation Experiments: Accounting for Input Uncertainty," Operations Research, INFORMS, vol. 49(5), pages 744-758, October.
    • Handle: RePEc:inm:oropre:v:49:y:2001:i:5:p:744-758
    DOI: 10.1287/opre.49.5.744.10606
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/opre.49.5.744.10606
    Download Restriction: no
    File URL: https://libkey.io/10.1287/opre.49.5.744.10606?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. 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.
    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. 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. J. C. Helton & F. J. Davis, 2002. "Illustration of Sampling‐Based Methods for Uncertainty and Sensitivity Analysis," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 591-622, June.
    3. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Property values associated with the failure of individual links in a system with multiple weak and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    4. Hou, Tianfeng & Nuyens, Dirk & Roels, Staf & Janssen, Hans, 2019. "Quasi-Monte Carlo based uncertainty analysis: Sampling efficiency and error estimation in engineering applications," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    5. Aven, Terje, 2020. "Three influential risk foundation papers from the 80s and 90s: Are they still state-of-the-art?," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    6. Durga Rao Karanki & Hari Shankar Kushwaha & Ajit Kumar Verma & Srividya Ajit, 2009. "Uncertainty Analysis Based on Probability Bounds (P‐Box) Approach in Probabilistic Safety Assessment," Risk Analysis, John Wiley & Sons, vol. 29(5), pages 662-675, May.
    7. Emanuele Borgonovo & Gordon B. Hazen & Elmar Plischke, 2016. "A Common Rationale for Global Sensitivity Measures and Their Estimation," Risk Analysis, John Wiley & Sons, vol. 36(10), pages 1871-1895, October.
    8. Terje Aven, 2010. "On the Need for Restricting the Probabilistic Analysis in Risk Assessments to Variability," Risk Analysis, John Wiley & Sons, vol. 30(3), pages 354-360, March.
    9. Julia J. Pet‐Armacost & Jose Sepulveda & Milton Sakude, 1999. "Monte Carlo Sensitivity Analysis of Unknown Parameters in Hazardous Materials Transportation Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 19(6), pages 1173-1184, December.
    10. Terje Aven, 2011. "On Different Types of Uncertainties in the Context of the Precautionary Principle," Risk Analysis, John Wiley & Sons, vol. 31(10), pages 1515-1525, October.
    11. M. Elisabeth Paté-Cornell & Robin L. Dillon, 2006. "The Respective Roles of Risk and Decision Analyses in Decision Support," Decision Analysis, INFORMS, vol. 3(4), pages 220-232, December.
    12. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2020. "Margins associated with loss of assured safety for systems with multiple weak links and strong links," Reliability Engineering and System Safety, Elsevier, vol. 195(C).
    13. Andrea Saltelli & Stefano Tarantola & Karen Chad, 1998. "Presenting Results from Model Based Studies to Decision‐Makers: Can Sensitivity Analysis Be a Defogging Agent?," Risk Analysis, John Wiley & Sons, vol. 18(6), pages 799-803, December.
    14. Sarazin, Gabriel & Morio, Jérôme & Lagnoux, Agnès & Balesdent, Mathieu & Brevault, Loïc, 2021. "Reliability-oriented sensitivity analysis in presence of data-driven epistemic uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    15. Ivan Lizaga & Borja Latorre & Leticia Gaspar & Ana Navas, 2020. "FingerPro: an R Package for Tracking the Provenance of Sediment," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(12), pages 3879-3894, September.
    16. Helton, Jon C. & Brooks, Dusty M. & Sallaberry, Cédric J., 2022. "Probability of Loss of Assured Safety in Systems with Multiple Time-Dependent Failure Modes: Incorporation of Delayed Link Failure in the Presence of Aleatory Uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    17. Emanuele Borgonovo, 2008. "Epistemic Uncertainty in the Ranking and Categorization of Probabilistic Safety Assessment Model Elements: Issues and Findings," Risk Analysis, John Wiley & Sons, vol. 28(4), pages 983-1001, August.
    18. Panggih Kusuma Ningrum & Iana Atanassova, 2024. "Annotation of scientific uncertainty using linguistic patterns," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(10), pages 6261-6285, October.
    19. Amirhossein Mokhtari & H. Christopher Frey, 2005. "Sensitivity Analysis of a Two‐Dimensional Probabilistic Risk Assessment Model Using Analysis of Variance," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1511-1529, December.
    20. Victor R. Vasquez & Wallace B. Whiting, 2005. "Accounting for Both Random Errors and Systematic Errors in Uncertainty Propagation Analysis of Computer Models Involving Experimental Measurements with Monte Carlo Methods," Risk Analysis, John Wiley & Sons, vol. 25(6), pages 1669-1681, December.

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;
    ;

    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:inm:oropre:v:49:y:2001:i:5:p:744-758. 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: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    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.