Scale Mixture of Gleser Distribution with an Application to Insurance Data

Neveka M. Olmos, Emilio Gómez-Déniz and Osvaldo Venegas ()
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Neveka M. Olmos: Departamento de Estadística y Ciencias de Datos, Facultad de Ciencias Básicas, Universidad de Antofagasta, Antofagasta 1240000, Chile
Emilio Gómez-Déniz: Department of Quantitative Methods in Economics, TIDES Institute, University of Las Palmas de Gran Canaria, 35017 Las Palmas de Gran Canaria, Spain
Osvaldo Venegas: Departamento de Ciencias Matemáticas y Físicas, Facultad de Ingeniería, Universidad Católica de Temuco, Temuco 4780000, Chile

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

Abstract: In this paper, the scale mixture of the Gleser (SMG) distribution is introduced. This new distribution is the product of a scale mixture between the Gleser (G) distribution and the Beta ( a , 1 ) distribution. The SMG distribution is an alternative to distributions with two parameters and a heavy right tail. We study its representation and some basic properties, maximum likelihood inference, and Fisher’s information matrix. We present an application to a real dataset in which the SMG distribution shows a better fit than two other known distributions.

Keywords: Gleser distribution; heavy-tailed distribution; maximum likelihood; scale mixture (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2024
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