On Generalized Gamma Distribution and Its Application to Survival Data

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.

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On Generalized Gamma Distribution and Its Application to Survival Data

International Journal of Statistics and Probability ◽

10.5539/ijsp.v8n5p85 ◽

2019 ◽

Vol 8 (5) ◽

pp. 85 ◽

Cited By ~ 2

Author(s):

Kiche J ◽

Oscar Ngesa ◽

George Orwa

Keyword(s):

Survival Analysis ◽

Gamma Distribution ◽

Survival Data ◽

Parametric Model ◽

Parametric Modeling ◽

Parametric Models ◽

Generalized Gamma Distribution ◽

Generalized Gamma ◽

Special Cases ◽

Two Parameter

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Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution

Statistics in Medicine ◽

10.1002/sim.2836 ◽

2007 ◽

Vol 26 (23) ◽

pp. 4352-4374 ◽

Cited By ~ 170

Author(s):

Christopher Cox ◽

Haitao Chu ◽

Michael F. Schneider ◽

Alvaro Muñoz

Keyword(s):

Survival Analysis ◽

Gamma Distribution ◽

Generalized Gamma Distribution ◽

Hazard Functions ◽

Generalized Gamma ◽

Parametric Survival ◽

Parametric Survival Analysis

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The Kumaraswamy generalized gamma distribution with application in survival analysis

Statistical Methodology ◽

10.1016/j.stamet.2011.04.001 ◽

2011 ◽

Vol 8 (5) ◽

pp. 411-433 ◽

Cited By ~ 37

Author(s):

Marcelino A.R. de Pascoa ◽

Edwin M.M. Ortega ◽

Gauss M. Cordeiro

Keyword(s):

Survival Analysis ◽

Gamma Distribution ◽

Generalized Gamma Distribution ◽

Generalized Gamma

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THEORETICAL PROPERTIES OF THE WEIGHTED GENERALIZED GAMMA AND RELATED DISTRIBUTIONS

Probability in the Engineering and Informational Sciences ◽

10.1017/s0269964815000078 ◽

2015 ◽

Vol 29 (3) ◽

pp. 421-432 ◽

Cited By ~ 1

Author(s):

Hewa A. Priyadarshani ◽

Broderick O. Oluyede

Keyword(s):

Gamma Distribution ◽

Hazard Function ◽

Gamma Model ◽

Generalized Gamma Distribution ◽

New Class ◽

Generalized Gamma ◽

Special Cases ◽

Entropy Measures ◽

Skewness Coefficient ◽

Coefficient Of Skewness

A new class of weighted generalized gamma distribution (WGGD) and related distributions are presented. Theoretical properties of the generalized gamma model, WGGD including the hazard function, reverse hazard function, moments, coefficient of variation, coefficient of skewness, coefficient of kurtosis, and entropy measures are derived. The results presented here generalizes the generalized gamma distribution and includes several distributions as special cases. The special cases include generalized gamma, weighted gamma, weighted exponential, weighted Weibull, weighted Rayleigh distributions, and their underlying or parent distributions.

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A Note on the Generalized (Positive) Cauchy Distribution

Canadian Mathematical Bulletin ◽

10.4153/cmb-1969-114-2 ◽

1969 ◽

Vol 12 (6) ◽

pp. 865-868 ◽

Cited By ~ 3

Author(s):

B. Raja Rao ◽

M. L. Garg

Keyword(s):

Gamma Distribution ◽

Cauchy Distribution ◽

Weibull Distributions ◽

Generalized Gamma Distribution ◽

Normal Variable ◽

Generalized Gamma ◽

Special Cases ◽

Chi Squared ◽

Image Position

In this note, a certain generalization of the Cauchy distribution is obtained, using the result of Malik [2].The generalized gamma distribution having the density(1)is introduced by Stacy [1], who studied some of its properties. As remarked by Stacy [1], the familiar gamma, chi, chi-squared, exponential and Weibull distributions are special cases of (1), as are the distributions of certain functions of a normal variable - viz.

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