Abstract
In Bayesian spatially varying parameter models the covariates’ coefficients in a regression model are allowed to change smoothly in space. A Markov random field is adopted as an improper prior distribution for the area-specific spatial effects. We demonstrate that the posterior distribution is a proper probability distribution.
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