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A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling
Subject area: Science,Engineering and Technology · Area of research: Sample survey
Abstract
In this study, a new exponential ratio-type estimator for estimating the population mean using two auxiliary variables in double sampling is proposed. The bias and mean squared error (MSE) of the proposed estimator are derived. The efficiency of the proposed estimator is compared theoretically with some existing estimators such as the usual sample mean estimator, the classical ratio estimator, and other exponential estimators. An empirical study using real-life data is conducted to examine the performance of the estimator. The results indicate that the proposed estimator has the smallest mean square error and the highest relative efficiency among the estimators considered. Hence, the estimator is recommended for practical applications in survey sampling where auxiliary information is available.
Keywords
Double Sampling, Auxiliary Variable, Exponential Estimator, Ratio Estimator, Mean Square Error.
References
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[2] Chand, L. (1975). Some Ratio-type Estimators Based on Two or More Auxiliary Variables.
[3] Cochran, W. G. (1977). Sampling Techniques (3rd ed.). Wiley.
[4] Faweya O., Ajayi E. and Akinyemi O. (2023). A New Ratio Type Estimator for Double Sampling with Two Auxiliary Variables. 8(2), International Journal of Innovative Science and Research Technology. 2162 - 2167.
[5] Kadilar, G. (2016). A New Exponential Type Estimator For the Population Mean in Simple Random Sampling. Journal of Modern Applied Statistical Methods, 15(2): 207-204.
[6] Khan, M. (2016). A Ratio Chain Type Exponential Estimator For Finite Population Mean Using Double Sampling. SpringerPlus 5(1): 86.
[7] Khare, B.B., Srivastava U. and Kumar K. (2013). A Generalized Chain Ratio in Regression For Population Mean Using Two Auxiliary Characters in Sample Survey. Journal of Scientific Research, 57, 147 – 153.
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How to cite this paper
@article{1715360,
author = {Faweya, Olanrewaju, Abifade, Victor Oluwatobi, Akinyemi, Oluwadare, Ayodele, Oluwasola Joshua, Oyinloye, Adedeji Adigun},
title = {A New Exponential Ratio-Type Estimator for Population Mean Using Two Auxiliary Variables in Double Sampling},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {9},
number = {9},
pages = {1795-1799},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1715360.pdf},
abstract = {In this study, a new exponential ratio-type estimator for estimating the population mean using two auxiliary variables in double sampling is proposed. The bias and mean squared error (MSE) of the proposed estimator are derived. The efficiency of the proposed estimator is compared theoretically with some existing estimators such as the usual sample mean estimator, the classical ratio estimator, and other exponential estimators. An empirical study using real-life data is conducted to examine the performance of the estimator. The results indicate that the proposed estimator has the smallest mean square error and the highest relative efficiency among the estimators considered. Hence, the estimator is recommended for practical applications in survey sampling where auxiliary information is available.},
keywords = {Double Sampling, Auxiliary Variable, Exponential Estimator, Ratio Estimator, Mean Square Error.},
month = {March},
doi = {https://doi.org/10.64388/IREV9I9-1715360}
}