Estimation of parameters in a two-component mixture generalized gamma distribution
C. Radhakrishna, A. V. Dattatreya Rao, G. V. S. R. Anjaneyulu
Abstract
C. Radhakrishna, A. V. Dattatreya Rao, G. V. S. R. Anjaneyulu
Abstract
Stacy (1962) introduced the Generalized Gamma Distribution (GGD) as follows : pdf: x > 0, b,c,θ > 0 where G(θ) is the Gamma function. This model is interesting since it includes both the Weibull and gamma distributions as special cases. As stated by Kao (1959), one has to use mixture distributions to analyse the data from life-testing experiments where there are two types of failures viz., sudden catastrophic failures and wear-out failures. In this paper an attempt is made to derive moment and M.L. estimators of the parameters of two-component mixture GGD defined by ; ,where is the GGD as mentioned above.
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Stacy (1962) introduced the Generalized Gamma Distribution (GGD) as follows : pdf: x > 0, b,c,θ > 0 where G(θ) is the Gamma function. This model is interesting since it includes both the Weibull and gamma distributions as special cases. As stated by Kao (1959), one has to use mixture distributions to analyse the data from life-testing experiments where there are two types of failures viz., sudden catastrophic failures and wear-out failures. In this paper an attempt is made to derive moment and M.L. estimators of the parameters of two-component mixture GGD defined by ; ,where is the GGD as mentioned above.
Key concepts: Generalized gamma distribution, Generalized integer gamma distribution, Gamma distribution, Weibull distribution, Component (thermodynamics), Estimator, Applied mathematics, Mathematics