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2014•AIP conference proceedingsRequires access

A new form of bivariate generalized Poisson regression model

Pouya Faroughi, Noriszura Ismail

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Abstract

This paper introduces a new form of bivariate generalized Poisson (BGP) regression which can be fitted to bivariate and correlated count data with covariates. The BGP regression suggested in this study can be fitted not only to bivariate count data with positive, zero or negative correlations, but also to underdispersed or overdispersed bivariate count data. Applications of bivariate Poisson (BP) regression and the new BGP regression are illustrated on Malaysian motor insurance data.

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What this paper is about

This paper introduces a new form of bivariate generalized Poisson (BGP) regression which can be fitted to bivariate and correlated count data with covariates. The BGP regression suggested in this study can be fitted not only to bivariate count data with positive, zero or negative correlations, but also to underdispersed or overdispersed bivariate count data. Applications of bivariate Poisson (BP) regression and the new BGP regression are illustrated on Malaysian motor insurance data.

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Available abstract

This paper introduces a new form of bivariate generalized Poisson (BGP) regression which can be fitted to bivariate and correlated count data with covariates. The BGP regression suggested in this study can be fitted not only to bivariate count data with positive, zero or negative correlations, but also to underdispersed or overdispersed bivariate count data. Applications of bivariate Poisson (BP) regression and the new BGP regression are illustrated on Malaysian motor insurance data.

Key concepts: Bivariate analysis, Poisson regression, Poisson distribution, Statistics, Bivariate data, Count data, Mathematics, Covariate

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