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A New Generalized Class of Distributions: Properties and Estimation Based on Type-I Censored Samples

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  • Zubair Ahmad

    (Quaid-i-Azam University 45320)

Abstract

This article introduces a new generalized family of distributions, which is a generalization of the exponentiated and transmuted family of distributions. A special model of this family, namely, new generalized Weibull distribution is considered in detail. General expressions for the mathematical properties of the proposed family are derived. Maximum likelihood estimates of the unknown parameters are obtained. A simulation study is done to evaluate the performances of the maximum likelihood estimators. Furthermore, estimation based on Type-I censored samples is also discussed. Finally, the superiority of the new proposal is illustrated empirically by analyzing a real-life application.

Suggested Citation

  • Zubair Ahmad, 2020. "A New Generalized Class of Distributions: Properties and Estimation Based on Type-I Censored Samples," Annals of Data Science, Springer, vol. 7(2), pages 243-256, June.
    • Handle: RePEc:spr:aodasc:v:7:y:2020:i:2:d:10.1007_s40745-018-0160-5
    DOI: 10.1007/s40745-018-0160-5
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    References listed on IDEAS

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    1. Broderick O. Oluyede & Shujiao Huang & Mavis Pararai, 2014. "A New Class of Generalized Dagum Distribution with Applications to Income and Lifetime Data," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 3(2), pages 1-8.
    2. Nadarajah, Saralees & Gupta, Arjun K., 2007. "A generalized gamma distribution with application to drought data," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 74(1), pages 1-7.
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