Abstract
This paper deals with the development of a new Maximum Likelihood (ML) estimator for semi-variogram parameters in ordinary Kriging, based upon the assumption of a multi-normal distribution of the Kriging cross-validation errors. The paper discusses the difference between the proposed ML formulation and previously developed algorithms, showing its advantages, also in view of an approximate analysis of the uncertainty that the semi-variogram parameter estimates may induced on the Kriging estimates.
An example of application of the proposed method is carried out for the estimation of yearly average precipitation over the Veneto Region in Italy.
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© 1999 Springer Science+Business Media Dordrecht
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Todini, E., Pellegrini, F. (1999). A Maximum Likelihood Estimator for Semi-Variogram Parameters in Kriging. In: Gómez-Hernández, J., Soares, A., Froidevaux, R. (eds) geoENV II — Geostatistics for Environmental Applications. Quantitative Geology and Geostatistics, vol 10. Springer, Dordrecht. https://doi.org/10.1007/978-94-015-9297-0_16
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DOI: https://doi.org/10.1007/978-94-015-9297-0_16
Publisher Name: Springer, Dordrecht
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