IDEAS home Printed from https://ideas.repec.org/a/csb/stintr/v14y2013i1p161-170.html
   My bibliography  Save this article

A linear model for uniformity trial experiments

Author

Listed:
  • Alok K. Shukla
  • Subhash K. Yadav
  • G. C. Mishra

Abstract

Uniformity trial experiments are required to assess fertility variation in agricultural land. Several models have appeared in literature, of which Fairfield Smith’s Variance Law assuming a nonlinear relationship between the coefficient of variation (C.V.) and a plot size has been extensively used in uniformity trial studies. A linear model has been proposed for uniformity trial experiments and it has shown better results as compared to existing models. The expression for point of maximum curvature for the proposed model is much simpler as compared to the model of Fairfield Smith. The appropriateness of the proposed model has also been verified with the help of a data set.

Suggested Citation

  • Alok K. Shukla & Subhash K. Yadav & G. C. Mishra, 2013. "A linear model for uniformity trial experiments," Statistics in Transition new series, Główny Urząd Statystyczny (Polska), vol. 14(1), pages 161-170, March.
    • Handle: RePEc:csb:stintr:v:14:y:2013:i:1:p:161-170
    as

    Download full text from publisher

    File URL: http://index.stat.gov.pl/repec/files/csb/stintr/csb_stintr_v14_14_i1_n11.pdf
    Download Restriction: no
    ---><---

    Citations

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


    Cited by:

    1. Shukla Alok Kumar & Yadav Subhash Kumar, 2020. "New linear model for optimal cluster size in cluster sampling," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 189-200, June.
    2. Alok Kumar Shukla & Subhash Kumar Yadav, 2020. "New linear model for optimal cluster size in cluster sampling," Statistics in Transition New Series, Polish Statistical Association, vol. 21(2), pages 189-200, June.

    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:1:p:161-170. 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.