摘要：Given two spatial data sets collected over the same geographical region, a common question of interest is the differences between these two data sets. The data may have been collected at two time points and the differences represent how the data has changed over the intervening time period. Or they may be data on two sub-populations and the differences then describe where and how these two subpopulations vary relative to each other. We consider the problem of objectively highlighting the differences between two spatial data sets, and showing these differences on a map. Specifically, we assume that the data sets are collected over a lattice, and model the values of one set as a function of those of the other data set, taking into account the inherent spatial structure. The model is a hierarchical model with spatial errors whose specification controls the amount of smoothing applied to the data. Additional covariates may be added to the model to explore more complex relationships between the two data sets. We apply the method to study the number of commuters to a town as obtained from cellular Call Detail Records, comparing them to Census data, and also model the commuter numbers with underlying population and distance away from the town.We also study differences in the number of visitors to the town during a St. Patrick’s Day parade with visitor numbers on other days.
关键词：Bayesian hierarchical model; differences between maps; human mobility; spatial data
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