IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v14y2013i2p201-216.html
   My bibliography  Save this article

The class of estimators of finite population mean using incomplete multi-auxiliary information

Author

Listed:
  • Meenakshi Srivastava
  • Neha Garg

Abstract

In this paper, a class of estimators is considered for estimating the mean of the finite population utilizing available incomplete multi-auxiliary information. Some special cases of this class of estimators are considered. The approximate expressions for bias and mean square error of the suggested estimators have also been derived and theoretical results are numerically supported.

Suggested Citation

  • Meenakshi Srivastava & Neha Garg, 2013. "The class of estimators of finite population mean using incomplete multi-auxiliary information," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(2), pages 201-216, June.
    • Handle: RePEc:csb:stintr:v:14:y:2013:i:2:p:201-216
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v14_2013_i2_n3.pdf
    Download Restriction: no
    ---><---

    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:csb:stintr:v:14:y:2013:i:2:p:201-216. 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: Beata Witek (email available below). General contact details of provider: https://edirc.repec.org/data/gusgvpl.html .

    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.