A proposed reparametrization of gamma distribution for the analysis of data of rainfall-runoff driven pollution

  • Bernardo Lagos Universidad de Concepción.
  • G. Ferreira Universidad de Concepción.
  • M. Valenzuela Universidad de Concepción.
Palabras clave: Gamma distribution, Maximum likelihood estimators, Moment estimators, Probability weighted moment estimators, Weighted least squares estimators, Water pollution and watershed.


A generalized gamma (GG) distribution of four parameters was first introduced by Amoroso 1925, and since then, different distributions emerged as subclasses of this model. This model is commonly used to model lifetime data or data with a right skewed unimodal density function. In this article, we use a reparameterization of the GG distribution that is compared with other usual two-parameter distributions, Weibull, generalized exponential (Gupta and Kundu 1999), and gamma, using a real data set with a high coefficient of asymmetry and kurtosis (Valenzuela M. 2009). Akaike's information criterion and Bayesian information criterion indicates that our reparametrization of the gamma distribution is better. Besides a Monte Carlo simulation study, shows the behavior of five estimation methods: least squared, weighted least squared, moments, probability weighted moments and maximum likelihood methods.


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Cómo citar
Lagos, B., Ferreira, G., & Valenzuela, M. (2011). A proposed reparametrization of gamma distribution for the analysis of data of rainfall-runoff driven pollution. Proyecciones. Journal of Mathematics, 30(3), 415-439. https://doi.org/10.4067/S0716-09172011000300009