IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v19y1995i3p265-282.html
   My bibliography  Save this article

Exact computation of the least trimmed squares estimate in simple linear regression

Author

Listed:
  • Hossjer, Ola

Abstract

No abstract is available for this item.

Suggested Citation

  • Hossjer, Ola, 1995. "Exact computation of the least trimmed squares estimate in simple linear regression," Computational Statistics & Data Analysis, Elsevier, vol. 19(3), pages 265-282, March.
    • Handle: RePEc:eee:csdana:v:19:y:1995:i:3:p:265-282
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/0167-9473(95)92697-V
    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. Hawkins, Douglas M., 1993. "The feasible set algorithm for least median of squares regression," Computational Statistics & Data Analysis, Elsevier, vol. 16(1), pages 81-101, June.
    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. Agullo, Jose, 2001. "New algorithms for computing the least trimmed squares regression estimator," Computational Statistics & Data Analysis, Elsevier, vol. 36(4), pages 425-439, 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. Neath, Andrew A. & Cavanaugh, Joseph E., 2000. "A regression model selection criterion based on bootstrap bumping for use with resistant fitting," Computational Statistics & Data Analysis, Elsevier, vol. 35(2), pages 155-169, December.
    2. Nunkesser, Robin & Morell, Oliver, 2010. "An evolutionary algorithm for robust regression," Computational Statistics & Data Analysis, Elsevier, vol. 54(12), pages 3242-3248, December.
    3. Nunkesser, Robin & Morell, Oliver, 2008. "Evolutionary algorithms for robust methods," Technical Reports 2008,29, Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen.
    4. Hawkins, Douglas M. & Olive, David J., 1999. "Improved feasible solution algorithms for high breakdown estimation," Computational Statistics & Data Analysis, Elsevier, vol. 30(1), pages 1-11, March.
    5. Marco Cattaneo & Andrea Wiencierz, 2014. "On the implementation of LIR: the case of simple linear regression with interval data," Computational Statistics, Springer, vol. 29(3), pages 743-767, June.
    6. Li, Lei M., 2005. "An algorithm for computing exact least-trimmed squares estimate of simple linear regression with constraints," Computational Statistics & Data Analysis, Elsevier, vol. 48(4), pages 717-734, April.
    7. Hawkins, Douglas M. & Olive, David, 1999. "Applications and algorithms for least trimmed sum of absolute deviations regression," Computational Statistics & Data Analysis, Elsevier, vol. 32(2), pages 119-134, December.
    8. Hawkins, Douglas M., 1995. "Convergence of the feasible solution algorithm for least median of squares regression," Computational Statistics & Data Analysis, Elsevier, vol. 19(5), pages 519-538, May.
    9. Mount, David M. & Netanyahu, Nathan S. & Romanik, Kathleen & Silverman, Ruth & Wu, Angela Y., 2007. "A practical approximation algorithm for the LMS line estimator," Computational Statistics & Data Analysis, Elsevier, vol. 51(5), pages 2461-2486, February.
    10. Bradu, Dan & Hawkins, Douglas M., 1995. "An Anscombe type robust regression statistic," Computational Statistics & Data Analysis, Elsevier, vol. 20(4), pages 355-386, October.
    11. Maronna, Ricardo A. & Barrera, Matías Salibian & Yohai, Víctor J., 2000. "Improving bias-robustness of regression estimates through projections," Statistics & Probability Letters, Elsevier, vol. 47(2), pages 149-158, 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:eee:csdana:v:19:y:1995:i:3:p:265-282. 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/csda .

    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.