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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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Identification Number: 10.3390/a15010016

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: 19 Mar 2024 01:12
URI: http://eprints.lse.ac.uk/id/eprint/113616

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