Ordinary Kriging

Historically, ordinary kriging was the first improvement of simple kriging, whose roots predate geostatistics (Goldberg, 1962; Cressie, 1990). We have seen that simple kriging requires knowledge of the mean to solve the problem of finding weights that minimize the variance of the estimation error. Ordinary kriging elegantly discards the requirement by filtering out the mean, taking advantage of Corollary 2.11. And by removing the mean from the estimator, the entire formulation becomes independent from the mean, as both the weights and the estimation variance in the simple kriging Algorithm 2.1 were already independent from the mean.