IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v47y2018i6p1442-1458.html
   My bibliography  Save this article

A study on the chain ratio-ratio-type exponential estimator for finite population variance

Author

Listed:
  • Housila P. Singh
  • Surya K. Pal
  • Anita Yadav

Abstract

This paper considers the problem of estimating the population variance S2y of the study variable y using the auxiliary information in sample surveys. We have suggested the (i) chain ratio-type estimator (on the lines of Kadilar and Cingi (2003)), (ii) chain ratio-ratio-type exponential estimator and their generalized version [on the lines of Singh and Pal (2015)] and studied their properties under large sample approximation. Conditions are obtained under which the proposed estimators are more efficient than usual unbiased estimator s2y and Isaki (1893) ratio estimator. Improved version of the suggested class of estimators is also given along with its properties. An empirical study is carried out in support of the present study.

Suggested Citation

  • Housila P. Singh & Surya K. Pal & Anita Yadav, 2018. "A study on the chain ratio-ratio-type exponential estimator for finite population variance," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(6), pages 1442-1458, March.
    • Handle: RePEc:taf:lstaxx:v:47:y:2018:i:6:p:1442-1458
    DOI: 10.1080/03610926.2017.1321124
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2017.1321124
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/03610926.2017.1321124?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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:taf:lstaxx:v:47:y:2018:i:6:p:1442-1458. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.