Ninth International Geostatistics Congress, Oslo, Norway
June 11 – 15, 2012
 
 
 
 
 
 
 

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. PelŠez , Northern Catholic University (CL)

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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