In this paper we propose a generalization of the Shapiro and Botha (1991) approach that allows one to obtain flexible spatio-temporal stationary variogram models. It is shown that if the weighted least squares criterion is chosen, the fitting of such models to pilot estimations of the variogram can be easily carried out by solving a quadratic programming problem. The work also includes an application to real data and a simulation study in order to illustrate the performance of the proposed space-time dependency modeling.
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