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 those changes.

中文翻译：

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具有时空变化系数的贝叶斯回归

为了研究气候变量对墨西哥某些疾病发病率的影响，我们提出了一个时空变化系数回归模型。为此，我们在贝叶斯上下文中引入了一个新的时空相关过程先验，具有相同分布的正态边缘分布和联合多元正态分布。我们研究了它的特性并描述了引起的依赖性。我们的结果表明，气候变量对特定疾病发病率的影响在空间和时间上并不是恒定的，我们提出的模型能够捕捉和量化这些变化。