Data from: Bayesian hierarchical models for spatially misaligned data in R

Andrew O. Finley, Sudipto Banerjee & Bruce D. Cook
Spatial misalignment occurs when at least one of multiple outcome variables is missing at an observed location. For spatial data, prediction of these missing observations should be informed by within location association among outcomes and by proximate locations where measurements were recorded. This study details and illustrates a Bayesian regression framework for modelling spatially misaligned multivariate data. Particular attention is paid to developing valid probability models capable of estimating parameter posterior distributions and propagating uncertainty...
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