Published

2013-01-01

The Family of Log-Skew-Normal Alpha-Power Distributions using Precipitation Data

La familia de distribuciones alfa-potencia log-skew-normal usando datos de precipitación

Keywords:

symmetry, Fisher information matrix, Kurtosis, Likelihood ratio test, Maximum likelihood estimator. (en)
Asimetría, curtosis, estimador máxima verosimilitud, matriz de información de Fisher, test de razón de verosimilitud. (es)

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Authors

  • Guillermo Martínez-Flórez Universidad de Córdoba. Departamento de Matemáticas y Estadística
  • Sandra Vergara-Cardozo Universidad Nacional de Colombia. Facultad de Ciencias. Departamento de Estadística
  • Luz Mery González Universidad Nacional de Colombia. Facultad de Ciencias. Departamento de Estadística
We present a new set of distributions for positive data based on a skewnormal alpha-power (PSN) model including a new parameter which in turn makes the log-skew-normal alpha-power (LPSN) model more flexible than both the log-normal (LN) model and log-skew-normal (LSN) model. The LPSN model contains the LN model and LSN model as special cases. Furthermore, it models positive data with asymmetry and kurtosis larger than the one permitted by the LN distribution. Precipitation data illustrates the usefulness of the LPSN model being less influenced by outliers.

Presentamos una nueva familia de distribuciones para datos positivos basada en el modelo skew-normal alpha-power (PSN), incluyendo un nuevo parámetro el cual hace el modelo log-skew-normal alpha-power (LPSN) más flexible que los modelos log-normal (LN) y log-skew-normal (LSN). El modelo LPSN contiene el modelo LN y el modelo LSN como casos particulares. Además, modela datos positivos con asimetría y curtosis más allá de lo permitido por la distribución LN. Datos de precipitación ilustran la utilidad del modelo LPSN siendo menos influenciado por outliers.

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