Bayesian modeling and clustering for spatio-temporal areal data: An application to Italian unemployment
时空区域数据的贝叶斯建模与聚类:意大利失业率应用
Spatio-temporal areal data can be seen as a collection of time series which are spatially correlated according to a specific neighboring structure. Incorporating the temporal and spatial dimension into a statistical model poses challenges regarding the underlying theoretical framework as well as the implementation of efficient computational methods. We propose to include spatio-temporal random effects using a conditional autoregressive prior, where the temporal correlation…