An expectation-maximization algorithm for the exponential-generalized inverse Gaussian regression model with varying dispersion and shape for modelling the aggregate claim amount

This article presents the Exponential-Generalized Inverse Gaussian regression model with varying dispersion and shape. The EGIG is a general distribution family which, under the adopted modelling framework, can provide the appropriate level of flexibility to fit moderate costs with high frequencies...

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Bibliographic Details

Published in:	Risks (Basel) Vol. 9; no. 1; pp. 1 - 17
Main Authors:	Tzougas, George, Jeong, Himchan
Format:	Journal Article
Language:	English
Published:	Basel MDPI 01.01.2021 MDPI AG
Subjects:	Algorithms Behavior dispersion and shape parameters EM Algorithm Exponential-Generalized Inverse Gaussian Distribution heavy-tailed losses Insurance premiums Life insurance non-life insurance Random variables regression models for the mean regression models for the mean, dispersion and shape parameters Reinsurance
ISSN:	2227-9091, 2227-9091
Online Access:	Get full text
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