Bayesian regression with spatiotemporal varying coefficients.

Abstract

To study the impact of climate variables on morbidity of some diseases in Mexico, we propose a spatiotemporal varying coefficients regression model. For that we introduce a new spatiotemporal-dependent process prior, in a Bayesian context, with identically distributed normal marginal distributions and joint multivariate normal distribution. We study its properties and characterise the dependence induced. Our results show that the effect of climate variables, on the incidence of specific diseases, is not constant across space and time and our proposed model is able to capture and quantify thosechanges.