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Efficient Estimation of Two-Parameter Xgamma Distribution Parameters Using Ranked Set Sampling Design

Author

Listed:
  • Amer Ibrahim Al-Omari

    (Department of Mathematics, Faculty of Science, Al al-Bayt University, Mafraq 25113, Jordan)

  • SidAhmed Benchiha

    (Department of Mathematics, University of Djillali Liabes, BP 89, Sidi Bel Abbes 22000, Algeria)

  • Ibrahim M. Almanjahie

    (Department of Mathematics, College of Science, King Khalid University, Abha 62529, Saudi Arabia
    Statistical Research and Studies Support Unit, King Khalid University, Abha 62529, Saudi Arabia)

Abstract

An efficient method such as ranked set sampling is used for estimating the population parameters when the actual observation measurement is expensive and complicated. In this paper, we consider the problem of estimating the two-parameter xgamma (TPXG) distribution parameters under the ranked set sampling as well as the simple random sampling design. Various estimation methods, including the weighted least-square estimator, maximum likelihood estimators, least-square estimator, Cramer–von Mises, the maximum product of spacings estimators, and Anderson–Darling estimators, are considered. A comparison between the ranked set sampling and simple random sampling estimators, with the same number of measurement units, is conducted using a simulation study in terms of the bias, mean squared errors, and efficiency of estimators. The merit of the ranked set sampling estimators is examined using real data of bank customers. The results indicate that estimations using the ranked set sampling method are more efficient than the simple random sampling competitor considered in this study.

Suggested Citation

  • Amer Ibrahim Al-Omari & SidAhmed Benchiha & Ibrahim M. Almanjahie, 2022. "Efficient Estimation of Two-Parameter Xgamma Distribution Parameters Using Ranked Set Sampling Design," Mathematics, MDPI, vol. 10(17), pages 1-18, September.
    • Handle: RePEc:gam:jmathe:v:10:y:2022:i:17:p:3170-:d:905636
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    References listed on IDEAS

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    Cited by:

    1. Heba F. Nagy & Amer Ibrahim Al-Omari & Amal S. Hassan & Ghadah A. Alomani, 2022. "Improved Estimation of the Inverted Kumaraswamy Distribution Parameters Based on Ranked Set Sampling with an Application to Real Data," Mathematics, MDPI, vol. 10(21), pages 1-19, November.

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