Prediction by Regression and kriging for Spatial Data with Application

This study deals with the prediction of the non-stationary spatial stochastic process. The prediction is done by two techniques which are regression technique (generalized least square estimation) and universal kriging technique. As it is familiar, that the non-stationary stochastic process has a trend (mean) as a linear or non-linear model. By this process we can find covariance function from knowing the variogram function and the latter is...