IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v47y1993i2p329-338.html
   My bibliography  Save this article

Simultaneous Estimation of Independent Normal Mean Vectors with Unknown Covariance Matrices

Author

Listed:
  • Krishnamoorthy, K.
  • Sarkar, S. K.

Abstract

Based on independent samples from several multivariate normal populations, possibly of different dimensions, the problem of simultaneous estimation of the mean vectors is considered assuming that the covariance matrices are unknown. Two loss functions, the sum of usual quadratic losses and the sum of arbitrary quadratic losses, are used. A class of minimax estimators generalizing the James-Stein estimator is obtained. It is shown that these estimators improve the usual set of sample mean vectors uniformly under the sum of quadratic losses. This result is extended to the sum of arbitrary quadratic losses under some restrictions on the covariance matrices.

Suggested Citation

  • Krishnamoorthy, K. & Sarkar, S. K., 1993. "Simultaneous Estimation of Independent Normal Mean Vectors with Unknown Covariance Matrices," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 329-338, November.
    • Handle: RePEc:eee:jmvana:v:47:y:1993:i:2:p:329-338
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(83)71086-9
    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.

    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:jmvana:v:47:y:1993:i:2:p:329-338. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.