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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Vydané v:	Risks (Basel) Ročník 9; číslo 1; s. 1 - 17
Hlavní autori:	Tzougas, George, Jeong, Himchan
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Basel MDPI 01.01.2021 MDPI AG
Predmet:	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
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