Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/77124
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Type: Conference paper
Title: Extensions of the parametric inference of spatial covariances by maximum likelihood
Author: Dowd, P.
Pardo-Iguzquiza, E.
Citation: Proceedings of the Ninth Geostatistics Conference, held in Oslo, 11-15 June, 2012 / P. Abrahamsen, R. Hauge and O. Kolbjørnsen (eds.): pp.129-141
Publisher: Springer
Publisher Place: Netherlands
Issue Date: 2012
Series/Report no.: Quantitative Geology and Geostatistics; 17
ISBN: 9789400741522
Conference Name: International Geostatistics Congress (9th : 2012 : Oslo)
Statement of
Responsibility: 
Peter A. Dowd and Eulogio Pardo-Igúzquiza
Abstract: The limitations of the maximum likelihood method for estimating spatial covariance parameters are: the assumption that the experimental data follow a multi-dimensional Gaussian distribution, biased estimates, impracticality for large data sets and the common assumption of a polynomial drift. The advantages are easy evaluation of parameter uncertainty, no information loss in binning and the ability to include additional information using a Bayesian framework. We provide extensions to overcome the disadvantages whilst maintaining the advantages.We provide an algorithm for obtaining covariance estimates for non-Gaussian data using Gaussian maximum likelihood. We provide a means of generating unbiased estimates of spatial covariance parameters without increasing the estimation variance. We overcome the impracticality for larger data sets by an approximation to the complete maximum likelihood. Finally, we extend the polynomial drift to other forms.
Rights: © Springer Science+Business Media Dordrecht 2012
RMID: 0020125420
DOI: 10.1007/978-94-007-4153-9_11
Appears in Collections:Civil and Environmental Engineering publications

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