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Ninth International Geostatistics Congress, Oslo, Norway
June 11 – 15, 2012 |
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No Paper Available |
Session: |
Theory 1 |
Abstract No.: |
O-035 |
Title: |
Sequential simulation with iterative methods |
Author(s): |
D. Arroyo, Northern Catholic University (CL)
X. Emery, University of Chile (CL)
M. Peláez , Northern Catholic University (CL)
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Abstract: |
The sequential Gaussian algorithm is widely used to simulate Gaussian random fields. In practice, the determination of the successive conditional distributions only uses the information available in a moving neighborhood centered on the target location, which provokes a loss of accuracy with respect to a unique neighborhood implementation. In order to reduce this loss of accuracy, iterative methods for solving large kriging systems of equations (namely, the Gauss-Seidel and Generalized Minimal Residual methods) are used to improve the determination of the conditional distributions, taking the results obtained in a moving neighborhood as a first approximation. Numerical experiments are presented to show the proposed strategies and the improvements in the reproduction of the correlation structure of the simulated field. |
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Copyright 2012 International Geostatistics Congress
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