Abstract
GCINFE, an ANSI FORTRAN-77 coded computer program for statistical inference of polynomial generalized covariance parameters, is examined in this paper. The generalized covariance function describes a nonstationary random field within the framework of the theory of intrinsic random functions of order k. The program utilizes four different estimation methods: minimum norm, minimum variance unbiased quadratic, minimum variance unbiased quadratic iterative and maximum likelihood. An important feature of these methods is that they provide a measure of uncertainty of the estimated parameters as defined by the standard deviation of the estimation error. The sampling distribution statistics of the four different methods evaluated through the Monte Carlo simulation technique are also presented for an example of the generalized covariance model.
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