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On Generalized Gamma Distribution and Its Application to Survival Data

Author

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  • Kiche J
  • Oscar Ngesa
  • George Orwa

Abstract

The generalized gamma distribution is a continuous probability distribution with three parameters. It is a generalization of the two-parameter gamma distribution. Since many distributions commonly used for parametric models in survival analysis (such as the Exponential distribution , the Weibull distribution and the Gamma distribution) are special cases of the generalized gamma, it is sometimes used to determine which parametric model is appropriate for a given set of data. Generalized gamma distribution is one of the distributions used in frailty modeling. In this study , it is shown that generalized gamma distribution has three sub-families and its application to the analysis of a survival data has also been explored. The parametric modeling approach has been carried out to find the expected results.

Suggested Citation

  • Kiche J & Oscar Ngesa & George Orwa, 2019. "On Generalized Gamma Distribution and Its Application to Survival Data," International Journal of Statistics and Probability, Canadian Center of Science and Education, vol. 8(5), pages 85-102, September.
    • Handle: RePEc:ibn:ijspjl:v:8:y:2019:i:5:p:85
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    References listed on IDEAS

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    1. Park, Sung Y. & Bera, Anil K., 2009. "Maximum entropy autoregressive conditional heteroskedasticity model," Journal of Econometrics, Elsevier, vol. 150(2), pages 219-230, June.
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    3. 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.
    4. Jiang, R. & Murthy, D.N.P., 2011. "A study of Weibull shape parameter: Properties and significance," Reliability Engineering and System Safety, Elsevier, vol. 96(12), pages 1619-1626.
    5. Dadpay, Ali & Soofi, Ehsan S. & Soyer, Refik, 2007. "Information measures for generalized gamma family," Journal of Econometrics, Elsevier, vol. 138(2), pages 568-585, June.
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    Cited by:

    1. Katikas, Loukas & Dimitriadis, Panayiotis & Koutsoyiannis, Demetris & Kontos, Themistoklis & Kyriakidis, Phaedon, 2021. "A stochastic simulation scheme for the long-term persistence, heavy-tailed and double periodic behavior of observational and reanalysis wind time-series," Applied Energy, Elsevier, vol. 295(C).
    2. Ben Boukai, 2021. "The Generalized Gamma distribution as a useful RND under Heston's stochastic volatility model," Papers 2108.07937, arXiv.org, revised Aug 2021.
    3. Korolev, Victor & Zeifman, Alexander, 2021. "Bounds for convergence rate in laws of large numbers for mixed Poisson random sums," Statistics & Probability Letters, Elsevier, vol. 168(C).
    4. Luca Pratelli & Pietro Rigo, 2021. "Convergence in Total Variation of Random Sums," Mathematics, MDPI, vol. 9(2), pages 1-11, January.

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    More about this item

    Keywords

    generalized gamma; sub-families; Kullback-Leibler divergence;
    All these keywords.

    JEL classification:

    • R00 - Urban, Rural, Regional, Real Estate, and Transportation Economics - - General - - - General
    • Z0 - Other Special Topics - - General

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