A Weighted Skew-Logistic Distribution with Applications to Environmental Data

Isaac Cortés, Jimmy Reyes and Yuri A. Iriarte ()
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Isaac Cortés: Facultad de Ciencias Básicas, Universidad Arturo Prat, Avenida Arturo Prat 2120, Iquique 1110939, Chile
Jimmy Reyes: Departamento de Estadística y Ciencia de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile
Yuri A. Iriarte: Departamento de Estadística y Ciencia de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile

Mathematics, 2024, vol. 12, issue 9, 1-21

Abstract: Skewness and bimodality properties are frequently observed when analyzing environmental data such as wind speeds, precipitation levels, and ambient temperatures. As an alternative to modeling data exhibiting these properties, we propose a flexible extension of the skew-logistic distribution. The proposal corresponds to a weighted version of the skewed logistic distribution, defined by a parametric weight function that allows shapes with up to three modes for the resulting density. Parameter estimation via the maximum likelihood approach is discussed. Simulation experiments are carried out to evaluate the performance of the estimators. Applications to environmental data illustrating the utility of the proposal are presented.

Keywords: bimodality; density; environmental data; maximum likelihood; moments; skewness; skew-logistic distribution; weighted distribution (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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