IDEAS home Printed from https://ideas.repec.org/a/spr/stpapr/v55y2014i4p1001-1018.html
   My bibliography  Save this article

Sufficient jackknife-after-bootstrap method for detection of influential observations in linear regression models

Author

Listed:
  • Ufuk Beyaztas
  • Aylin Alin

Abstract

In this study, we adapt sufficient bootstrap into the jackknife-after-bootstrap (JaB) algorithm. The performances of the sufficient and conventional JaB methods have been compared for detecting influential observations in linear regression. Comparison is based on two real-world examples and an extensive designed simulation study. Design includes different sample sizes and various modeling scenarios. The results reveal that proposed method is a good competitor for conventional JaB method with less standard error and amount of computation. Copyright Springer-Verlag Berlin Heidelberg 2014

Suggested Citation

  • Ufuk Beyaztas & Aylin Alin, 2014. "Sufficient jackknife-after-bootstrap method for detection of influential observations in linear regression models," Statistical Papers, Springer, vol. 55(4), pages 1001-1018, November.
    • Handle: RePEc:spr:stpapr:v:55:y:2014:i:4:p:1001-1018
    DOI: 10.1007/s00362-013-0548-4
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s00362-013-0548-4
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s00362-013-0548-4?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
    ---><---

    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. Michael Martin & Steven Roberts, 2010. "Jackknife-after-bootstrap regression influence diagnostics," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 22(2), pages 257-269.
    2. Singh, Sarjinder & Sedory, Stephen A., 2011. "Sufficient bootstrapping," Computational Statistics & Data Analysis, Elsevier, vol. 55(4), pages 1629-1637, April.
    3. Whasoo Bae & Soonyoung Hwang & Choongrak Kim, 2008. "Influence diagnostics in the varying coefficient model with longitudinal data," Computational Statistics, Springer, vol. 23(2), pages 185-196, April.
    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. Ufuk Beyaztas & Beste H. Beyaztas, 2019. "On Jackknife-After-Bootstrap Method for Dependent Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1613-1632, April.

    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. Ufuk Beyaztas & Beste H. Beyaztas, 2019. "On Jackknife-After-Bootstrap Method for Dependent Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(4), pages 1613-1632, April.
    2. Sayed A. Mostafa & Ibrahim A. Ahmad, 2021. "Kernel Density Estimation Based on the Distinct Units in Sampling with Replacement," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 83(2), pages 507-547, November.
    3. J. M. Muñoz-Pichardo & J. L. Moreno-Rebollo & R. Pino-Mejías & M. D. Cubiles Vega, 2019. "Influence measures in beta regression models through distance between distributions," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 103(2), pages 163-185, June.
    4. Ufuk Beyaztas & Aylin Alin & Michael A. Martin, 2014. "Robust BCa-JaB method as a diagnostic tool for linear regression models," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1593-1610, July.

    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:spr:stpapr:v:55:y:2014:i:4:p:1001-1018. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.