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Maximum likelihood estimation under a finite mixture of generalized exponential distributions based on censored data

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  • Saieed Ateya

Abstract

In this paper, the identifiability of a finite mixture of generalized exponential distributions (GE(τ, α)) is proved and the maximum likelihood estimates (MLE’s) of the parameters are obtained using EM algorithm based on a general form of right-censored failure times. The results are specialized to type-I and type-II censored samples. A real data set is introduced and analyzed using a mixture of two GE(τ, α) distributions and also using a mixture of two Weibull(α, β) distributions. A comparison is carried out between the mentioned mixtures based on the corresponding Kolmogorov–Smirnov (K–S) test statistic to emphasize that the GE(τ, α) mixture model fits the data better than the other mixture model. Copyright Springer-Verlag Berlin Heidelberg 2014

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  • Saieed Ateya, 2014. "Maximum likelihood estimation under a finite mixture of generalized exponential distributions based on censored data," Statistical Papers, Springer, vol. 55(2), pages 311-325, May.
    • Handle: RePEc:spr:stpapr:v:55:y:2014:i:2:p:311-325
    DOI: 10.1007/s00362-012-0480-z
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    References listed on IDEAS

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    Cited by:

    1. Nenghui Kuang & Bingquan Liu, 2018. "Least squares estimator for $$\alpha $$ α -sub-fractional bridges," Statistical Papers, Springer, vol. 59(3), pages 893-912, September.
    2. Camila Borelli Zeller & Celso Rômulo Barbosa Cabral & Víctor Hugo Lachos & Luis Benites, 2019. "Finite mixture of regression models for censored data based on scale mixtures of normal distributions," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 13(1), pages 89-116, March.
    3. M. Alizadeh & S. Rezaei & S. Bagheri & S. Nadarajah, 2015. "Efficient estimation for the generalized exponential distribution," Statistical Papers, Springer, vol. 56(4), pages 1015-1031, November.
    4. Omar M. Bdair & Mohammad Z. Raqab, 2022. "Prediction of future censored lifetimes from mixture exponential distribution," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 85(7), pages 833-857, October.

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