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Improved Mean Estimation for a Finite Population with Twofold Auxiliary Variables Under Simple Random Sampling

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Abstract

The goal of this article is to suggest an improved estimator for assessing the mean of a population using a twofold auxiliary variable under simple random sampling. To the first order of approximation, the numerical expression of the bias and mean square error are derived. We use actual data sets and simulation study to measure the efficiency of the suggested estimator. The efficiency of the suggested estimator is evaluated relative to the preliminary estimators using the MSE criterion. An empirical investigation strengthens up the theoretical findings. Theoretical analysis reveals that the suggested estimator performs better as compared to existing counterparts. The outcome of actual data and a simulation study stated the proposed estimator performs better as compared to minimum MSE and higher PRE compared to existing estimators.

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Authors and Affiliations

  1. Department of Statistics, Abdul Wali Khan University, Mardan, Pakistan

    Sohaib Ahmad & Muhammad Aamir

  2. Department of Statistics, University of Wah, Wah Cantt, Pakistan

    Javid Shabbir

  3. Department of Statistics, Quaid-I-Azam University, Islamabad, Pakistan

    Sardar Hussain

  4. Foundation University Medical College, Foundation University School of Health Sciences, DHA-I, Islamabad, 44000, Pakistan

    Kalim Ullah

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  1. Sohaib Ahmad
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  2. Javid Shabbir
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  3. Muhammad Aamir
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  4. Sardar Hussain
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  5. Kalim Ullah
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Contributions

SA wrote the main manuscript. JS and MA reviewed the main manuscript SH and KU helped in the revised manuscript.

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Correspondence to Sohaib Ahmad.

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Ahmad, S., Shabbir, J., Aamir, M. et al. Improved Mean Estimation for a Finite Population with Twofold Auxiliary Variables Under Simple Random Sampling. Int. J. Appl. Comput. Math 10, 31 (2024). https://doi.org/10.1007/s40819-023-01624-1

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