IDEAS home Printed from https://ideas.repec.org/a/wly/apsmbi/v24y2008i5p369-371.html
   My bibliography  Save this article

Statistical methods in performance analysis

Author

Listed:
  • Maria Rosaria D'Esposito
  • Michel Tenenhaus

Abstract

No abstract is available for this item.

Suggested Citation

  • Maria Rosaria D'Esposito & Michel Tenenhaus, 2008. "Statistical methods in performance analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 369-371, September.
    • Handle: RePEc:wly:apsmbi:v:24:y:2008:i:5:p:369-371
    DOI: 10.1002/asmb.723
    as

    Download full text from publisher

    File URL: https://doi.org/10.1002/asmb.723
    Download Restriction: no
    File URL: https://libkey.io/10.1002/asmb.723?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. Franco Peracchi & Andrei V. Tanase, 2008. "On estimating the conditional expected shortfall," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 471-493, September.
    2. Carolyn J. Heinrich, 2008. "Advancing public sector performance analysis," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 24(5), pages 373-389, September.
    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. Leorato, Samantha & Peracchi, Franco & Tanase, Andrei V., 2012. "Asymptotically efficient estimation of the conditional expected shortfall," Computational Statistics & Data Analysis, Elsevier, vol. 56(4), pages 768-784.
    2. Saralees Nadarajah & Bo Zhang & Stephen Chan, 2014. "Estimation methods for expected shortfall," Quantitative Finance, Taylor & Francis Journals, vol. 14(2), pages 271-291, February.
    3. Zhongde Luo, 2020. "Nonparametric kernel estimation of CVaR under $$\alpha $$α-mixing sequences," Statistical Papers, Springer, vol. 61(2), pages 615-643, April.
    4. Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2020. "Computation of Expected Shortfall by fast detection of worst scenarios," Working Papers hal-02619589, HAL.
    5. Rockafellar, R.T. & Royset, J.O. & Miranda, S.I., 2014. "Superquantile regression with applications to buffered reliability, uncertainty quantification, and conditional value-at-risk," European Journal of Operational Research, Elsevier, vol. 234(1), pages 140-154.
    6. So Yeon Chun & Alexander Shapiro & Stan Uryasev, 2012. "Conditional Value-at-Risk and Average Value-at-Risk: Estimation and Asymptotics," Operations Research, INFORMS, vol. 60(4), pages 739-756, August.
    7. Julia S. Mehlitz & Benjamin R. Auer, 2021. "Time‐varying dynamics of expected shortfall in commodity futures markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(6), pages 895-925, June.
    8. Bruno Bouchard & Adil Reghai & Benjamin Virrion, 2020. "Computation of Expected Shortfall by fast detection of worst scenarios," Papers 2005.12593, arXiv.org.
    9. Pettas, Nikolaos & Giannikos, Ioannis, 2014. "Evaluating the delivery performance of public spending programs from an efficiency perspective," Evaluation and Program Planning, Elsevier, vol. 45(C), pages 140-150.
    10. Denis Chetverikov & Yukun Liu & Aleh Tsyvinski, 2022. "Weighted-average quantile regression," Papers 2203.03032, arXiv.org.

    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:apsmbi:v:24:y:2008:i:5:p:369-371. 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/10.1002/(ISSN)1526-4025 .

    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.