IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v94y1996i3p488-504.html
   My bibliography  Save this article

Approximate representation of probabilistic data in expert systems

Author

Listed:
  • Sarkar, Sumit
  • Mendelson, Haim
  • Storey, Veda C.

Abstract

No abstract is available for this item.

Suggested Citation

  • Sarkar, Sumit & Mendelson, Haim & Storey, Veda C., 1996. "Approximate representation of probabilistic data in expert systems," European Journal of Operational Research, Elsevier, vol. 94(3), pages 488-504, November.
  • Handle: RePEc:eee:ejores:v:94:y:1996:i:3:p:488-504
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0377-2217(95)00130-1
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Eric Rosenberg & Alan Gleit, 1994. "Quantitative Methods in Credit Management: A Survey," Operations Research, INFORMS, vol. 42(4), pages 589-613, August.
    2. Robert L. Winkler & Roy M. Poses, 1993. "Evaluating and Combining Physicians' Probabilities of Survival in an Intensive Care Unit," Management Science, INFORMS, vol. 39(12), pages 1526-1543, 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. Thomas Wainwright, 2011. "Elite Knowledges: Framing Risk and the Geographies of Credit," Environment and Planning A, , vol. 43(3), pages 650-665, March.
    2. Robert B. Avery & Kenneth P. Brevoort & Glenn Canner, 2012. "Does Credit Scoring Produce a Disparate Impact?," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 40, pages 65-114, December.
    3. Ozer, Muammer, 2007. "Reducing the demand uncertainties at the fuzzy-front-end of developing new online services," Research Policy, Elsevier, vol. 36(9), pages 1372-1387, November.
    4. Fernandes, Guilherme Barreto & Artes, Rinaldo, 2016. "Spatial dependence in credit risk and its improvement in credit scoring," European Journal of Operational Research, Elsevier, vol. 249(2), pages 517-524.
    5. Chernonog, Tatyana & Avinadav, Tal, 2016. "A two-state partially observable Markov decision process with three actionsAuthor-Name: Ben-Zvi, Tal," European Journal of Operational Research, Elsevier, vol. 254(3), pages 957-967.
    6. Loutfi, Ahmad Amine, 2022. "A framework for evaluating the business deployability of digital footprint based models for consumer credit," Journal of Business Research, Elsevier, vol. 152(C), pages 473-486.
    7. Hussein A. Abdou & John Pointon, 2011. "Credit Scoring, Statistical Techniques And Evaluation Criteria: A Review Of The Literature," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 59-88, April.
    8. Walter Krämer & Michael Bücker, 2011. "Probleme des Qualitätsvergleichs von Kreditausfallprognosen," AStA Wirtschafts- und Sozialstatistisches Archiv, Springer;Deutsche Statistische Gesellschaft - German Statistical Society, vol. 5(1), pages 39-58, March.
    9. Rais Ahmad Itoo & A. Selvarasu & José António Filipe, 2015. "Loan Products and Credit Scoring by Commercial Banks (India)," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 5(1), pages 851-851.
    10. Karl Waldmann, 1998. "On granting credit in a random environment," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 47(1), pages 99-115, February.
    11. Hurley, W. J. & Lior, D. U., 2002. "Combining expert judgment: On the performance of trimmed mean vote aggregation procedures in the presence of strategic voting," European Journal of Operational Research, Elsevier, vol. 140(1), pages 142-147, July.
    12. Crook, Jonathan N. & Edelman, David B. & Thomas, Lyn C., 2007. "Recent developments in consumer credit risk assessment," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1447-1465, December.
    13. James K. Hammitt & Alexander I. Shlyakhter, 1999. "The Expected Value of Information and the Probability of Surprise," Risk Analysis, John Wiley & Sons, vol. 19(1), pages 135-152, February.
    14. Andreea Costea, 2017. "A Quantitative Approach to Credit Risk Management in the Underwriting Process for the Retail Portfolio," Romanian Economic Journal, Department of International Business and Economics from the Academy of Economic Studies Bucharest, vol. 20(63), pages 157-186, March.
    15. Zhixin Liu & Ping He & Bo Chen, 2019. "A Markov decision model for consumer term-loan collections," Review of Quantitative Finance and Accounting, Springer, vol. 52(4), pages 1043-1064, May.
    16. Hand, David J., 2009. "Mining the past to determine the future: Problems and possibilities," International Journal of Forecasting, Elsevier, vol. 25(3), pages 441-451, July.
    17. Liu, Fan & Hua, Zhongsheng & Lim, Andrew, 2015. "Identifying future defaulters: A hierarchical Bayesian method," European Journal of Operational Research, Elsevier, vol. 241(1), pages 202-211.
    18. James K. Hammitt & Yifan Zhang, 2013. "Combining Experts’ Judgments: Comparison of Algorithmic Methods Using Synthetic Data," Risk Analysis, John Wiley & Sons, vol. 33(1), pages 109-120, January.
    19. R. Winkler & Javier Muñoz & José Cervera & José Bernardo & Gail Blattenberger & Joseph Kadane & Dennis Lindley & Allan Murphy & Robert Oliver & David Ríos-Insua, 1996. "Scoring rules and the evaluation of probabilities," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 5(1), pages 1-60, June.
    20. Simon, Mark & Shrader, Rodney C., 2012. "Entrepreneurial actions and optimistic overconfidence: The role of motivated reasoning in new product introductions," Journal of Business Venturing, Elsevier, vol. 27(3), pages 291-309.

    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:eee:ejores:v:94:y:1996:i:3:p:488-504. 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: http://www.elsevier.com/locate/eor .

    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.