Evaluation of empirical Bayesian kriging

Abstract Using Bayesian bootstrap as the informative prior distribution is a key feature of the empirical Bayesian kriging method. We evaluate correctness of the method using two large simulation experiments. We also compare empirical Bayesian kriging performance with several popular geostatistical models implemented in R using two real datasets: the average annual precipitation in South Africa and the daytime land surface temperature satellite data. Results show that empirical Bayesian kriging performs better than other predictors, and increasingly so with data complexity.