IDEAS home Printed from https://ideas.repec.org/a/eee/csdana/v53y2008i2p394-404.html
   My bibliography  Save this article

Minimum MSE regression estimator with estimated population quantities of auxiliary variables

Author

Listed:
  • Park, Mingue
  • Cho, HyungJun

Abstract

Construction of a regression estimator in which the population means of auxiliary variables are estimated with a larger sample is considered. Using the variances of the estimated population means, and the correlation between auxiliary variables and the variable of interest, a design consistent regression estimator that has minimum model mean squared error under a working model is derived. A limited simulation study shows that the minimum model mean squared error regression estimator performs well compared to the generalized least squares regression estimator, even when the working model is inappropriate.

Suggested Citation

  • Park, Mingue & Cho, HyungJun, 2008. "Minimum MSE regression estimator with estimated population quantities of auxiliary variables," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 394-404, December.
    • Handle: RePEc:eee:csdana:v:53:y:2008:i:2:p:394-404
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-9473(08)00390-3
    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. P. Bardsley & R. L. Chambers, 1984. "Multipurpose Estimation from Unbalanced Samples," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 33(3), pages 290-299, November.
    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. Jean-Francois Beaumont & Cynthia Bocci, 2008. "Another look at ridge calibration," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 5-20.
    2. Miller, Elton N. & Andrews, Gregory, 1993. "Factors influencing landholders' investments in soil conservation activities," 1993 Conference (37th), February 9-11, 1993, Sydney, Australia 147759, Australian Agricultural and Resource Economics Society.
    3. Alessio Guandalini & Claudio Ceccarelli, 2022. "Impact measurement and dimension reduction of auxiliary variables in calibration estimator using the Shapley decomposition," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(4), pages 759-784, October.

    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:53:y:2008:i:2:p:394-404. 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.