Flexible Power-Normal Models with Applications

Guillermo Martínez-Flórez, Diego I. Gallardo, Osvaldo Venegas, Heleno Bolfarine and Héctor W. Gómez
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Guillermo Martínez-Flórez: Departamento de Matemáticas y Estadística, Facultad de Ciencias, Universidad de Córdoba, Córdoba 2300, Colombia
Diego I. Gallardo: Departamento de Matemática, Facultad de Ingeniería, Universidad de Atacama, Copiapó 1530000, Chile
Osvaldo Venegas: Departamento de Ciencias Matemáticas y Físicas, Facultad de Ingeniería, Universidad Católica de Temuco, Temuco 4780000, Chile
Heleno Bolfarine: Departamento de Estatística, IME, Universidade de São Paulo, São Paulo 05508-090, Brazil
Héctor W. Gómez: Departamento de Matemáticas, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile

Mathematics, 2021, vol. 9, issue 24, 1-15

Abstract: The main object of this paper is to propose a new asymmetric model more flexible than the generalized Gaussian model. The probability density function of the new model can assume bimodal or unimodal shapes, and one of the parameters controls the skewness of the model. Three simulation studies are reported and two real data applications illustrate the flexibility of the model compared with traditional proposals in the literature.

Keywords: power normal distribution; bimodal asymmetric distribution; moments; maximum likelihood estimators; fisher information matrix (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
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