New class of estimators for enhanced estimation of average production of peppermint yield utilising known auxiliary variable Online publication date: Thu, 04-Nov-2021
by S.K. Yadav; Dinesh K. Sharma; Kate Brown
International Journal of Mathematics in Operational Research (IJMOR), Vol. 20, No. 2, 2021
Abstract: The arithmetic mean is the best measure of central tendency for a homogenous population for the characteristics under study. Estimation can be improved by including auxiliary information and various estimators have been suggested in the literature. In this paper, a new class of estimators using known auxiliary parameters for estimation of the average yield of peppermint oil is suggested. The proposed estimator's sampling properties, the bias and mean squared error (MSE) up to the approximation of first order are studied. The suggested estimator is compared theoretically to some existing estimators of population mean that an auxiliary variable. The theoretical efficiency conditions are verified using real primary data collected from the Siddaur Block of Barabanki District at Uttar Pradesh State (India). The performances of various estimators are judged from their calculated MSEs using this primary data.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Mathematics in Operational Research (IJMOR):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook