Bayesian spatially varying coefficient models in the spBayes R package

03/07/2019 ∙ by Andrew O. Finley, et al. ∙ 0

This paper describes and illustrates the addition of the spSVC function to the spBayes R package. The spSVC function uses a computationally efficient Markov chain Monte Carlo algorithm detailed in FBG15 and extends current spBayes functions, that fit only space-varying intercept regression models, to fit independent or multivariate Gaussian process random effects for any set of columns in the regression design matrix. Newly added OpenMP parallelization options for spSVC are discussed and illustrated, as well as helper functions for joint and point-wise prediction and model fit diagnostics.



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