Title: New class of estimators for enhanced estimation of average production of peppermint yield utilising known auxiliary variable

Authors: S.K. Yadav; Dinesh K. Sharma; Kate Brown

Addresses: Department of Statistics, Babasaheb Bhimrao Ambedkar University, Lucknow – 226025, UP, India ' Department of Business, Management and Accounting, University of Maryland Eastern Shore, Princess Anne – 21853, MD, USA ' Department of Business, Management and Accounting, University of Maryland Eastern Shore, Princess Anne – 21853, MD, USA

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.

Keywords: primary variable; auxiliary variable; estimator; bias; mean squared error; MSE; PRE.

DOI: 10.1504/IJMOR.2021.118758

International Journal of Mathematics in Operational Research, 2021 Vol.20 No.2, pp.281 - 295

Received: 16 Jun 2020
Accepted: 27 Jul 2020
Published online: 04 Nov 2021 *

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