On MCMC sampling in hierarchical longitudinal models
Statistics and Computing
On smoothness properties of spatial processes
Journal of Multivariate Analysis
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Handbook of Mathematical Functions, With Formulas, Graphs, and Mathematical Tables,
Parallelizing MCMC for Bayesian spatiotemporal geostatistical models
Statistics and Computing
Parallel multivariate slice sampling
Statistics and Computing
Non-Gaussian modeling of spatial data using scale mixing of a unified skew Gaussian process
Journal of Multivariate Analysis
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An auxiliary variable method based on a slice sampler is shown to provide an attractive simulation-based model fitting strategy for fitting Bayesian models under proper priors. Though broadly applicable, we illustrate in the context of fitting spatial models for geo-referenced or point source data. Spatial modeling within a Bayesian framework offers inferential advantages and the slice sampler provides an algorithm which is essentially "off the shelf". Further potential advantages over importance sampling approaches and Metropolis approaches are noted and illustrative examples are supplied.