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A New Generalized Class of Exponential Factor-Type Estimators for Population Distribution Function Using Two Auxiliary Variables

Author

Listed:
  • Sohaib Ahmad
  • Muhammad Aamir
  • Sardar Hussain
  • Javid Shabbir
  • Erum Zahid
  • Khanyaluck Subkrajang
  • Anuwat Jirawattanapanit
  • Tahir Mehmood

Abstract

In this article, we propose a generalized class of exponential factor type estimators for estimation of the finite population distribution function (PDF) using an auxiliary variable in the form of the mean and rank of the auxiliary variable exist. The expressions of the bias and mean square error of the estimators are computed up to the first order approximation. The proposed estimators provide minimum mean square error as compared to all other considered estimators. Three real data sets are used to check the performance of the proposed estimators. Moreover, simulation studies are also carried out to observe the performances of the proposed estimators. The proposed estimators confirmed their superiority numerically as well as theoretically by producing efficient results as compared to all other competing estimators.

Suggested Citation

  • Sohaib Ahmad & Muhammad Aamir & Sardar Hussain & Javid Shabbir & Erum Zahid & Khanyaluck Subkrajang & Anuwat Jirawattanapanit & Tahir Mehmood, 2022. "A New Generalized Class of Exponential Factor-Type Estimators for Population Distribution Function Using Two Auxiliary Variables," Mathematical Problems in Engineering, Hindawi, vol. 2022, pages 1-13, August.
    • Handle: RePEc:hin:jnlmpe:2545517
    DOI: 10.1155/2022/2545517
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