IDEAS home Printed from https://ideas.repec.org/a/wut/journl/v1y2015p81-101id1126.html
   My bibliography  Save this article

Hybrid correlated data in risk assessment

Author

Listed:
  • Bogdan Rębiasz

Abstract

A method for evaluating the risks in a situation has been presented where parameters in the calculation are expressed in the form of dependent fuzzy numbers and probability distributions. The procedure of risk estimation combines stochastic simulation with the execution of arithmetic operations on interactive fuzzy numbers. In order to define operations on such numbers, non-linear programming is used. Relations between the parameters presented in the form of fuzzy numbers and probability distributions are expressed by means of interval regression. The results of computations indicate that the relations between parameters have a significant impact on the ratios characterizing risk.

Suggested Citation

  • Bogdan Rębiasz, 2015. "Hybrid correlated data in risk assessment," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 25(1), pages 81-101.
    • Handle: RePEc:wut:journl:v:1:y:2015:p:81-101:id:1126
    DOI: 10.5277/ord150105
    as

    Download full text from publisher

    File URL: https://ord.pwr.edu.pl/assets/papers_archive/1126%20-%20published.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.5277/ord150105?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. Lee, Haekwan & Tanaka, Hideo, 1999. "Upper and lower approximation models in interval regression using regression quantile techniques," European Journal of Operational Research, Elsevier, vol. 116(3), pages 653-666, August.
    2. J. Arlin Cooper & Scott Ferson & Lev Ginzburg, 1996. "Hybrid Processing of Stochastic and Subjective Uncertainty Data," Risk Analysis, John Wiley & Sons, vol. 16(6), pages 785-791, December.
    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. Bogdan Rębiasz, 2016. "New method of selecting efficient project portfolios in the presence of hybrid uncertainty," Operations Research and Decisions, Wroclaw University of Science and Technology, Faculty of Management, vol. 26(4), pages 65-90.
    2. Parvaneh Shahnoori & Glenn P. Jenkins, 2019. "The value of online banking to small and medium-sized enterprises: evidence from firms operating in the uae free trade zones," Applied Economics, Taylor & Francis Journals, vol. 51(37), pages 4046-4055, August.
    3. Parvaneh Shahnoori & Glenn P. Jenkins, 2018. "The Value of Online Banking to Small and Meduim-Sized Enterprises: Evidence From Firms Operating in The UAE From Trade Zones," Development Discussion Papers 2018-12, JDI Executive Programs.
    4. Wang, Hsiao-Fan & Hsu, Fei-Chen, 2009. "An integrated operation module for individual risk management," European Journal of Operational Research, Elsevier, vol. 198(2), pages 610-617, October.
    5. Junrui Xu & James H. Lambert, 2015. "Risk‐Cost‐Benefit Analysis for Transportation Corridors with Interval Uncertainties of Heterogeneous Data," Risk Analysis, John Wiley & Sons, vol. 35(4), pages 624-641, April.
    6. Dineswary Nadarajan & Saber Abdelall Mohamed Ahmed & Noor Fadiya Mohd Noor, 2023. "Seaport Network Efficiency Measurement Using Triangular and Trapezoidal Fuzzy Data Envelopment Analyses with Liner Shipping Connectivity Index Output," Mathematics, MDPI, vol. 11(6), pages 1-27, March.
    7. Guo, Peijun & Tanaka, Hideo, 2006. "Dual models for possibilistic regression analysis," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 253-266, November.
    8. Jorge De Andrés-Sánchez, 2024. "Calculating Insurance Claim Reserves with an Intuitionistic Fuzzy Chain-Ladder Method," Mathematics, MDPI, vol. 12(6), pages 1-24, March.
    9. Eduardo Conde, 2014. "A Minmax Regret Linear Regression Model Under Uncertainty in the Dependent Variable," Journal of Optimization Theory and Applications, Springer, vol. 160(2), pages 573-596, February.
    10. Hojati, Mehran & Bector, C. R. & Smimou, Kamal, 2005. "A simple method for computation of fuzzy linear regression," European Journal of Operational Research, Elsevier, vol. 166(1), pages 172-184, October.

    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:wut:journl:v:1:y:2015:p:81-101:id:1126. 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: Adam Kasperski (email available below). General contact details of provider: https://edirc.repec.org/data/iopwrpl.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.