SciELO - Scientific Electronic Library Online

vol.6 número4Comparación de resultados experimentales de un Venturi con simulación de dinámica de fluidos computacional índice de autoresíndice de materiabúsqueda de artículos
Home Pagelista alfabética de revistas  

Servicios Personalizados




Links relacionados

  • No hay artículos similaresSimilares en SciELO


Tecnología y ciencias del agua

versión On-line ISSN 2007-2422


CAMPOS-ARANDA, Daniel Francisco. Fitting of GPA, GLO and GEV Distributions with Trimmed L-moments (1, 0). Tecnol. cienc. agua [online]. 2015, vol.6, n.4, pp.153-167. ISSN 2007-2422.

Statistical moments have been used to characterize probability distributions and samples of observed data. This work briefly describes the theory of L-moments and trimmed L-moments (1,0), which can reduce the influence of the lowest value in a sample, in order to improve the fit and obtain more reliable extreme predictions. Recent equations found in the statistical literature that estimate the location, scale and shape of the probability distribution functions are cited, which are often used to analyze the frequencies of extreme hydrological data. These include the General Extreme Values (GEV), Generalized Logistic (GLO) and Generalized Pareto (GPA) equations. These three distributions were fitted with the methods of L-moments and trimmed L-moments (1,0) to 21 annual maximum flow registries from Hydrological Region No. 10 (Sinaloa). The quality of each fit was evaluated based on the standard error. The analysis of the results indicate that the GPA distribution provides the smallest fitting errors for 13 registries using the trimmed L-moments (1,0) and for the rest of the registries using L-moments. The conclusions suggest that the three probabilistic models studied can be applied with the trimmed L-moments (1,0) as an advanced version of the L-moments procedure which is universally used.

Palabras llave : L-moments; trimmed L-moments (1, 0); probability distributions GEV, GLO and GPA; standard error of fit; Hydrological Region No. 10 (Sinaloa).

        · resumen en Español     · texto en Español     · Español ( pdf )


Creative Commons License Todo el contenido de esta revista, excepto dónde está identificado, está bajo una Licencia Creative Commons