Conditional versus unconditional mean-squared prediction errors for Gaussian processes with constant but unknown mean

摘要

For prediction in a Gaussian random field, we give an explicit formulation of the conditional mean-squared prediction error (cmspe). If the prediction method is ordinary kriging, we find that this error in most applications is likely to be very close to the ordinary kriging variance. This is additionally demonstrated based on a case study. Finally, we discuss the difference between these two errors compared to the error introduced by using estimated instead of true covariance parameters.