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Different estimation methods for the parameters of the extended Burr XII distribution

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  • Ilhan Usta

Abstract

The extended three-parameter Burr XII (EBXII) distribution has recently attracted considerable attention for modeling data from various scientific fields since it yields a wide range of skewness and kurtosis values. However, it is well known that the parameter estimates have significant effects on the success of a distribution in real-life applications. In this study, modified moment estimators (MMEs) and modified probability-weighted moments estimators (MPWMEs) are used to estimate the parameters of the EBXII distribution. These two considered estimators are also compared with the commonly used maximum-likelihood, percentiles, least-squares and weighted least-squares estimators in terms of bias and efficiency via an extensive numerical simulation. The MMEs and MPWMEs are observed to perform well in varying sample cases, and the simulation results are supported with application through a real-life data set.

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  • Ilhan Usta, 2013. "Different estimation methods for the parameters of the extended Burr XII distribution," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 397-414, February.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:2:p:397-414
    DOI: 10.1080/02664763.2012.743974
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    References listed on IDEAS

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    1. M. E. Ghitany & S. Al-Awadhi, 2002. "Maximum likelihood estimation of Burr XII distribution parameters under random censoring," Journal of Applied Statistics, Taylor & Francis Journals, vol. 29(7), pages 955-965.
    2. Kundu, Debasis & Raqab, Mohammad Z., 2005. "Generalized Rayleigh distribution: different methods of estimations," Computational Statistics & Data Analysis, Elsevier, vol. 49(1), pages 187-200, April.
    3. Fu-Kwun Wang & Yung-Fu Cheng, 2010. "Robust regression for estimating the Burr XII parameters with outliers," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(5), pages 807-819.
    4. Shao, Quanxi & Chen, Yongqin D. & Zhang, Lu, 2008. "An extension of three-parameter Burr III distribution for low-flow frequency analysis," Computational Statistics & Data Analysis, Elsevier, vol. 52(3), pages 1304-1314, January.
    5. Shao, Quanxi, 2004. "Notes on maximum likelihood estimation for the three-parameter Burr XII distribution," Computational Statistics & Data Analysis, Elsevier, vol. 45(3), pages 675-687, April.
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    1. Shahzad Hussain & Sajjad Haider Bhatti & Tanvir Ahmad & Muhammad Ahmed Shehzad, 2021. "Parameter estimation of the Pareto distribution using least squares approaches blended with different rank methods and its applications in modeling natural catastrophes," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 107(2), pages 1693-1708, June.
    2. Klein, Ingo, 2017. "(Generalized) maximum cumulative direct, paired, and residual Φ entropy principle," FAU Discussion Papers in Economics 25/2017, Friedrich-Alexander University Erlangen-Nuremberg, Institute for Economics.
    3. Usta, Ilhan, 2016. "An innovative estimation method regarding Weibull parameters for wind energy applications," Energy, Elsevier, vol. 106(C), pages 301-314.
    4. Hassan M. Okasha & Abdulkareem M. Basheer & A. H. El-Baz, 2021. "Marshall–Olkin Extended Inverse Weibull Distribution: Different Methods of Estimations," Annals of Data Science, Springer, vol. 8(4), pages 769-784, December.

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