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Utilization of Priori Information in the Estimation of Population Mean for Time-Based Surveys

Author

Listed:
  • Sanjay Kumar

    (Central University of Rajasthan)

  • Priyanka Chhaparwal

    (University of Engineering and Management)

Abstract

Use of a priori information is very common at an estimation stage to form an estimator of a population parameter. Estimation problems can lead to more accurate and efficient estimates using prior information. In this study, we utilized the information from the past surveys along with the information available from the current surveys in the form of a hybrid exponentially weighted moving average to suggest the estimator of the population mean using a known coefficient of variation of the study variable for time-based surveys. We derived the expression of the mean square error of the suggested estimator and established the mathematical conditions to prove the efficiency of the suggested estimator. The results showed that the utilization of information from past surveys and current surveys excels the estimator's efficiency. A simulation study and a real-life example are provided to support using the suggested estimator.

Suggested Citation

  • Sanjay Kumar & Priyanka Chhaparwal, 2024. "Utilization of Priori Information in the Estimation of Population Mean for Time-Based Surveys," Annals of Data Science, Springer, vol. 11(5), pages 1675-1685, October.
    • Handle: RePEc:spr:aodasc:v:11:y:2024:i:5:d:10.1007_s40745-023-00472-6
    DOI: 10.1007/s40745-023-00472-6
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    References listed on IDEAS

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    1. Abhimanyu Singh Yadav & Sudhansu S. Maiti & Mahendra Saha, 2021. "The Inverse Xgamma Distribution: Statistical Properties and Different Methods of Estimation," Annals of Data Science, Springer, vol. 8(2), pages 275-293, June.
    2. Varun Agiwal, 2023. "Bayesian Estimation of Stress Strength Reliability from Inverse Chen Distribution with Application on Failure Time Data," Annals of Data Science, Springer, vol. 10(2), pages 317-347, April.
    3. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
    4. M. Shaaban & M. Yahya, 2023. "Comparison Between Dependent and Independent Ranked Set Sampling Designs for Parametric Estimation with Applications," Annals of Data Science, Springer, vol. 10(1), pages 167-182, February.
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