IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v101y2010i6p1400-1411.html
   My bibliography  Save this article

A new projection estimate for multivariate location with minimax bias

Author

Listed:
  • Adrover, Jorge G.
  • Yohai, Víctor J.

Abstract

The maximum asymptotic bias of an estimator is a global robustness measure of its performance. The projection median estimator for multivariate location shows a remarkable behavior regarding asymptotic bias. In this paper we consider a modification of the projection median estimator which renders an estimate with better bias performance for point mass contaminations (the worst situation for the projection median estimator). Moreover, it achieves the lowest bound for an equivariant estimate for point mass contaminations.

Suggested Citation

  • Adrover, Jorge G. & Yohai, Víctor J., 2010. "A new projection estimate for multivariate location with minimax bias," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1400-1411, July.
    • Handle: RePEc:eee:jmvana:v:101:y:2010:i:6:p:1400-1411
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(09)00226-7
    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. Kim, Jeankyung & Hwang, Jinsoo, 2001. "Asymptotic properties of location estimators based on projection depth," Statistics & Probability Letters, Elsevier, vol. 55(3), pages 293-299, December.
    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. Schmitt, Eric & Öllerer, Viktoria & Vakili, Kaveh, 2014. "The finite sample breakdown point of PCS," Statistics & Probability Letters, Elsevier, vol. 94(C), pages 214-220.

    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. Hwang, Jinsoo & Jorn, Hongsuk & Kim, Jeankyung, 2004. "On the performance of bivariate robust location estimators under contamination," Computational Statistics & Data Analysis, Elsevier, vol. 44(4), pages 587-601, January.

    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:jmvana:v:101:y:2010:i:6:p:1400-1411. 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/wps/find/journaldescription.cws_home/622892/description#description .

    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.