Mixed poisson regression models with varying dispersion arising from non-conjugate mixing distributions

Tzougas, George, Hong, Natalia and Ho, Ryan (2022) Mixed poisson regression models with varying dispersion arising from non-conjugate mixing distributions. Algorithms, 15 (1). ISSN 1999-4893

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Abstract

In this article we present a class of mixed Poisson regression models with varying dispersion arising from non-conjugate to the Poisson mixing distributions for modelling overdispersed claim counts in non-life insurance. The proposed family of models combined with the adopted modelling framework can provide sufficient flexibility for dealing with different levels of overdispersion. For illustrative purposes, the Poisson-lognormal regression model with regression structures on both its mean and dispersion parameters is employed for modelling claim count data from a motor insurance portfolio. Maximum likelihood estimation is carried out via an expectation-maximization type algorithm, which is developed for the proposed family of models and is demonstrated to perform satisfactorily.

Item Type:	Article
Official URL:	https://www.mdpi.com/journal/algorithms
Additional Information:	© 2021 The Authors
Divisions:	Statistics
Subjects:	H Social Sciences > HA Statistics
Date Deposited:	04 Feb 2022 12:00
Last Modified:	16 Nov 2024 08:03
URI:	http://eprints.lse.ac.uk/id/eprint/113616

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