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Efficient Estimation of the PDF and the CDF of the Frechet Distribution

Author

Listed:
  • F. Maleki

    (Islamic Azad University)

  • E. Deiri

    (Islamic Azad University)

Abstract

In this paper, we consider the estimation of the PDF and the CDF of the Frechet distribution. In this regard, following estimators are considered: uniformly minimum variance unbiased estimator, maximum likelihood estimator, percentile estimator, least squares estimator and weighted least squares estimator. To do so, analytical expressions are derived for the bias and the mean squared error. As the result of simulation studies and real data applications indicate, the ML estimator performs better than the others.

Suggested Citation

  • F. Maleki & E. Deiri, 2017. "Efficient Estimation of the PDF and the CDF of the Frechet Distribution," Annals of Data Science, Springer, vol. 4(2), pages 211-225, June.
    • Handle: RePEc:spr:aodasc:v:4:y:2017:i:2:d:10.1007_s40745-017-0100-9
    DOI: 10.1007/s40745-017-0100-9
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    Cited by:

    1. Amal S. Hassan & Salwa M. Assar & Kareem A. Ali & Heba F. Nagy, 2021. "Estimation of the density and cumulative distribution functions of the exponentiated Burr XII distribution," Statistics in Transition New Series, Polish Statistical Association, vol. 22(4), pages 171-189, December.
    2. Hassan Amal S. & Assar Salwa M. & Ali Kareem A. & Nagy Heba F., 2021. "Estimation of the density and cumulative distribution functions of the exponentiated Burr XII distribution," Statistics in Transition New Series, Polish Statistical Association, vol. 22(4), pages 171-189, December.

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