IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v12y2011i3p587-594.html
   My bibliography  Save this article

A general family of dual to ratio-cum-product estimator in sample surveys

Author

Listed:
  • Nirmala Sawan
  • Rajesh Singh
  • Manoj Kumar
  • Pankaj Chauhan
  • Florentin Smarandache

Abstract

This paper presents a family of dual to ratio-cum-product estimators for the finite population mean. Under simple random sampling without replacement (SRSWOR) scheme, expressions of the bias and mean-squared error (MSE) up to the first order of approximation are derived. We show that the proposed family is more efficient than usual unbiased estimator, ratio estimator, product estimator, Singh estimator (1967), Srivenkataramana (1980) and Bandyopadhyaya estimator (1980) and Singh et al. (2005) estimator. An empirical study is carried out to illustrate the performance of the constructed estimator over others.

Suggested Citation

  • Nirmala Sawan & Rajesh Singh & Manoj Kumar & Pankaj Chauhan & Florentin Smarandache, 2011. "A general family of dual to ratio-cum-product estimator in sample surveys," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 12(3), pages 587-594, December.
    • Handle: RePEc:csb:stintr:v:12:y:2011:i:3:p:587-594
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v12_2011_i3_n21.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Manoj Kumar & Shashi Bahl, 2006. "Class of dual to ratio estimators for double sampling," Statistical Papers, Springer, vol. 47(2), pages 319-326, March.
    2. M. Singh, 1967. "Ratio cum product method of estimation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 12(1), pages 34-42, December.
    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. B. K. Singh & S. Choudhury, 2012. "A class of chain ratio-cum-dual to ratio type estimator with two auxiliary characters under double sampling in sample surveys," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(3), pages 519-536, December.
    2. Narendra K. Jatwa & Rajesh Tailor & Housila P. Singh, 2013. "A Ratio-Cum-Product Estimator of Finite Population Mean in Systematic Sampling," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(3), pages 391-398, September.
    3. Giancarlo Diana & Pier Francesco Perri, 2007. "Estimation of finite population mean using multi-auxiliary information," Metron - International Journal of Statistics, Dipartimento di Statistica, Probabilità e Statistiche Applicate - University of Rome, vol. 0(1), pages 99-112.
    4. repec:exl:29stat:v:20:y:2019:i:3:p:81-96 is not listed on IDEAS
    5. Khare B. B. & Sinha R. R., 2019. "Estimation Of Product Of Two Population Means By Multi-Auxiliary Characters Under Double Sampling The Non-Respondents," Statistics in Transition New Series, Statistics Poland, vol. 20(3), pages 81-95, September.
    6. Thakur Narendra Singh & Shukla Diwakar, 2022. "Missing data estimation based on the chaining technique in survey sampling," Statistics in Transition New Series, Statistics Poland, vol. 23(4), pages 91-111, December.
    7. B. B. Khare & R. R. Sinha, 2019. "Estimation Of Product Of Two Population Means By Multi-Auxiliary Characters Under Double Sampling The Non-Respondents," Statistics in Transition New Series, Polish Statistical Association, vol. 20(3), pages 81-95, September.
    8. Housila Singh & Ramkrishna Solanki, 2013. "A new procedure for variance estimation in simple random sampling using auxiliary information," Statistical Papers, Springer, vol. 54(2), pages 479-497, May.
    9. Housila Singh & R. Biradar, 1992. "Almost unbiased ratio-cum-product estimators for the finite population mean," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 1(1), pages 19-29, December.
    10. A. K. P. C. Swain, 2012. "On classes of modified ratio type and regression-cum-ratio type estimators in sample surveys using two auxiliary variables," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 13(3), pages 473-494, December.
    11. Rajesh Singh & Rohan Mishra, 2023. "Ratio-cum-product Type Estimators for Rare and Hidden Clustered Population," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 33-53, May.

    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:12:y:2011:i:3:p:587-594. 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: 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.