Smoothing regional maps using empirical Bayes predictors
If the data to be mapped are values of a variable that are known only by region, then from the point of view of pure data summary, a map of the regions coded or colored according to the values of the variable is a very effective way of presenting both the data and the regional geography. This article will concentrate on the important case where the variable mapped is a rate. Since such rates have a nonconstant base, one is faced with a statistical comparison of regional data whose variances may be highly different. Thus, if the regional map is to be used to look for spatial patterns in the data, it is important to map smoothed values that take into account the spatial inhomogeneity of variances, as well as any spatial dependence between regions. -from Author
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