Cookies?
Library Header Image
LSE Research Online LSE Library Services

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

[img] Text (algorithms-15-00016-v2 (1)) - Published Version
Available under License Creative Commons Attribution.

Download (489kB)
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: 07 Feb 2022 09:15
URI: http://eprints.lse.ac.uk/id/eprint/113616

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year

View more statistics