Bayesian methods and software for spatial data analysis are generally now well established in the scientific community. Despite the wide application of spatial models, the analysis of multivariate spatial data using R-INLA has not been widely described in the existing literature. Therefore, the main objective of this article is to demonstrate that R-INLA is a convenient toolbox to analyse different types of multivariate spatial datasets. Additionally, this will be illustrated by analysing three datasets which are publicly available. Furthermore, the details and the R code of these analyses are provided to exemplify how to adjust multivariate spatial datasets with R-INLA.

翻译：尽管广泛应用了空间模型,但现有文献并未广泛描述使用R-INLA对多变空间数据的分析,因此,本条的主要目的是证明R-INLA是分析不同类型多变空间数据集的方便工具箱,此外,还将通过分析公开提供的三套数据集来说明这一点;此外,还提供这些分析的细节和R代码,以示范如何调整R-INLA的多变空间数据集。