PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models
PICAR: An Efficient Extendable Approach for Fitting Hierarchical Spatial Models
Hierarchical spatial models are very flexible and popular for a vast array of applications in areas such as ecology, social science, public health, and atmospheric science. It is common to carry out Bayesian inference for these models via Markov chain Monte Carlo (MCMC). Each iteration of the MCMC algorithm is …