Bayesian multivariate Poisson regression

The paper proposes a regression model for the multivariate Poisson distribution. So far inference in multivariate Poisson distributions has been prevented by the fact that computation of the probability mass function is difficult. Bayesian methods of inference are proposed which are organized around computational methods based on Gibbs sampling with data augmentation. The new methods are illustrated using artificial data as well as European forest damage data.