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Order Statistics of Generalized Topp–Leone Distribution with Application to Tissue Damage Proportions in Blood

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Abstract

Order statistic plays an important role in statistical theoretical and practical problems. In this paper, we derive algebraic expressions for both single and product moments of order statistics from generalized Topp–Leone (GTL) distribution. These expressions will be useful for computational purposes. Further, based on order statistics, we have obtained maximum likelihood estimators of the model parameters and uniformly minimum variance unbiased estimator for the model parameters of the GTL distribution. Finally, based on order statistics, Monte Carlo simulation study has been carried out to compare the performances of the proposed methods in terms of bias and mean square error, and a real life data set has been analyzed for illustrative purposes.

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ACKNOWLEDGMENTS

The authors would like to thank the Editors and the anonymous referees, for their valuable and very constructive comments, which have greatly improved the contents of the paper.

Funding

The second author extend his sincere appreciation to the National Natural Science Foundation of China (no. 12061091), the Yunnan Fundamental Research Projects (no. 202101AT070103) and the Doctoral Research Foundation of Yunnan Normal University (no. 00800205020503129).

Author information

Authors and Affiliations

  1. Department of Statistics, Central University of Haryana, Haryana, India

    Kumar Devendra

  2. School of Mathematics, Yunnan Normal University, Kunming, China

    Wang Liang

  3. Department of Statistics, St. Anthony’s College, Shillong, Meghalaya, India

    Dey Sanku

Authors
  1. Kumar Devendra
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  2. Wang Liang
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  3. Dey Sanku
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Corresponding authors

Correspondence to Kumar Devendra, Wang Liang or Dey Sanku.

Additional information

(Submitted by A. I. Volodin)

Kumar Devendra is a corresponding author

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Devendra, K., Liang, W. & Sanku, D. Order Statistics of Generalized Topp–Leone Distribution with Application to Tissue Damage Proportions in Blood. Lobachevskii J Math 44, 3673–3689 (2023). https://doi.org/10.1134/S199508022309007X

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  • DOI: https://doi.org/10.1134/S199508022309007X

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