(Translated by https://www.hiragana.jp/)
Improved separate ratio and product exponential type estimators in the case of post-stratification
IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v16y2015i1p53-64.html
   My bibliography  Save this article

Improved separate ratio and product exponential type estimators in the case of post-stratification

Author

Listed:
  • Rajesh Tailor
  • Hilal A. Lone

Abstract

This paper addressed the problem of estimation of finite population mean in the case of post-stratification. Improved separate ratio and product exponential type estimators in the case of post-stratification are suggested. The biases and mean squared errors of the suggested estimators are obtained up to the first degree of approximation. Theoretical and empirical studies have been done to demonstrate better efficiencies of the suggested estimators than other considered estimators.

Suggested Citation

  • Rajesh Tailor & Hilal A. Lone, 2015. "Improved separate ratio and product exponential type estimators in the case of post-stratification," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 16(1), pages 53-64, May.
  • Handle: RePEc:csb:stintr:v:16:y:2015:i:1:p:53-64
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v16_2015_i1_n4.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Hilal A. Lone & Rajesh Tailor, 2015. "Improved Separate Ratio And Product Exponential Type Estimators In The Case Of Post-Stratification," Statistics in Transition New Series, Polish Statistical Association, vol. 16(1), pages 53-64, March.

    More about this item

    Keywords

    finite population mean; post-stratification; bias; mean squared error;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

    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:csb:stintr:v:16:y:2015:i:1:p:53-64. 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.