A Maximum Likelihood Estimator for Semi-Variogram Parameters in Kriging
作者： Ezio Todini , Federica Pellegrini
DOI: 10.1007/978-94-015-9297-0_16
关键词: Likelihood function 、 Variogram 、 Efficient estimator 、 Bayes estimator 、 Mathematics 、 Applied mathematics 、 Estimation theory 、 Kriging 、 Restricted maximum likelihood 、 Bias of an estimator
摘要: This paper deals with the development of a new Maximum Likelihood (ML) estimator for semi-variogram parameters in ordinary Kriging, based upon assumption multi-normal distribution Kriging cross-validation errors. The discusses difference between proposed ML formulation and previously developed algorithms, showing its advantages, also view an approximate analysis uncertainty that parameter estimates may induced on estimates.
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