Title: Introducing new optimal class of Searls estimators of population mean using powered auxiliary parameters

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

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

Abstract: The sample mean, in addition to being the most appropriate estimator of mean of the population characteristic, has a significant sampling variance. According to Searls (1964), a constant multiple of the sample mean is a better estimator of the population mean. The use of a strongly correlated auxiliary variable often improves the estimator's performance. This article proposes a novel family of ratio estimators of the vernal Searls type that use known powered auxiliary parameters for the population mean. The proposed estimator's sampling properties are investigated up to the first order of approximation. The efficiency conditions are obtained by comparing the mean squared errors (MSE) of the introduced and competing estimators. These efficiency conditions are validated using both real and simulated datasets. The R programming is used to perform the numerical computation.

Keywords: study variable; auxiliary variable; simple random sampling; bias; mean squared errors; MSE; PRE.

DOI: 10.1504/IJOR.2024.137182

International Journal of Operational Research, 2024 Vol.49 No.3, pp.311 - 325

Received: 18 Jan 2021
Accepted: 10 Jun 2021
Published online: 04 Mar 2024 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article