Alternative Ratio Estimator of Population Mean in Simple Random Sampling

Abstract

An alternative ratio estimator is proposed for a finite population mean of a study variable Y in simple random sampling using information on the mean of an auxiliary variable X, which is highly correlated with Y. Expressions for the bias and the mean square error of the proposed estimator are obtained. Both analytical and numerical comparisons have shown the proposed alternative estimator to be more efficient than some existing ones. The bias of the proposed estimator is also found to be negligible for all populations considered, indicating that the estimator is as good as the regression estimator and better than the other estimators under consideration.

Calibration Approach Ratio Estimators of Population Median in Stratified Random Sampling Design

“…Motivated by Kuk and Mak [14] and Aladag and Cingi [1], a new ratio median estimator under one constraint is given as:…”

“…They also dealt with the estimation of population median in simple and stratified random sampling using auxiliary information such as mode, range and correlation coefficient. In existing literature, authors like: Aamir, Shabri, and Isaq [12], Baig, Masood and Tarray [13], Enang, Etuk, Ekpenyong and Akpan [14], Garcia and Cebrian [15], Gross [16], Jhaji and Bhangu [17], Meeden [18], Price [19], Sharma [20], Singh and Joarder [21], Singh, Singh and Martinez [22], Singh, Singh and Upadhyaya [23], Singh and Solanki [24], Solanki and Singh [25], Tracy, Singh and Arnab [26], have provided modification to the sample median estimator. Though, these proposed estimators are improvement over existing median estimators, no effort has yet been made to developing a median estimator using calibration approach.…”

A modified class of exponential-type estimator of population-mean in simple random sampling

“…In light of the above shortcomings, several authors have studied to improve the existing classical ratio and product estimators to increase efficiency and also give better options in decision making. [17], [19], [20], [15], [1], [21], [8], [9], [10], [18], [2], [3], [16], [7] and [6] are amongst authors who have contributed in one way or the other to the modification of the classical ratio estimator for the population mean of the study variable under simple random sampling without replacement (SRSWOR) scheme with extensions to other sampling techniques. This study is another attempt to propose an alternative estimator for the population mean using a combination of necessary scalars which is expected to have small-er relative bias and compare favourably with the linear regression estimator.…”

A Combined Family of Ratio Estimators for Population Mean using an Auxiliary Variable in Simple Random Sampling

“…Alternatively, some researchers have recommended combining ratio estimators in order to minimize the mean square error. For example, Enang, et al [20] proposed combining Singh & Tailor's [5] estimator with Kadilar & Cingi's [7] estimator to minimize the mean square error.…”