BAYESIAN MULTIVARIATE POISSON REGRESSION

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Bayesian Multivariate Poisson Regression for Models of Injury Count, by Severity (2006, methodology): “For ease of implementation, the following assumption is made for the trivariate Poisson distribution, as employed by Tsionas (2001) for his models of forest damage:”
Multivariate Poisson-Lognormal Models for Jointly Modeling Crash Frequency by Severity (2007, methodology): “Ma and Kockelman (16) adapted a multivariate Poisson (MVP) regression approach developed by Tsionas (17 ) to assess the effects of various covariates on multivariate crash counts by severity.”
Multivariate Negative Binomial Models for Insurance Claim Counts (2014, methodology): “Such limitation could be addressed through multi-factor models with examples that include the multivariate Poissonlog-normal model (Aitchison and Ho (1989)) and the latent Poisson-normal model (van Ophem (1999)).”
Modelling Dependence in a Ratemaking Procedure with Multivariate Poisson Regression Models (2010, methodology): “The first one, which we call the “common covariance model”, has been defined in Tsionas (2001) and the second one, the “full covariance model”, in Karlis and Meligkotsidou (2005).”
Bayesian multivariate Poisson models for insurance ratemaking (2011, unknown): “The first one, which we call the “common covariance model”, has been defined in Tsionas (2001) and the second one, the “full covariance model”, in Karlis and Meligkotsidou (2005).”