Estimation or simulation? That is the question
Contribuinte(s) |
UNIVERSIDADE DE SÃO PAULO |
---|---|
Data(s) |
20/10/2012
20/10/2012
2008
|
Resumo |
The issue of smoothing in kriging has been addressed either by estimation or simulation. The solution via estimation calls for postprocessing kriging estimates in order to correct the smoothing effect. Stochastic simulation provides equiprobable images presenting no smoothing and reproducing the covariance model. Consequently, these images reproduce both the sample histogram and the sample semivariogram. However, there is still a problem, which is the lack of local accuracy of simulated images. In this paper, a postprocessing algorithm for correcting the smoothing effect of ordinary kriging estimates is compared with sequential Gaussian simulation realizations. Based on samples drawn from exhaustive data sets, the postprocessing algorithm is shown to be superior to any individual simulation realization yet, at the expense of providing one deterministic estimate of the random function. National Council for Scientific and Technological Development[303505/2007-9] National Council for Scientific and Technological Development |
Identificador |
COMPUTATIONAL GEOSCIENCES, v.12, n.4, p.573-591, 2008 1420-0597 http://producao.usp.br/handle/BDPI/30317 10.1007/s10596-008-9096-8 |
Idioma(s) |
eng |
Publicador |
SPRINGER |
Relação |
Computational Geosciences |
Direitos |
restrictedAccess Copyright SPRINGER |
Palavras-Chave | #Ordinary kriging #Smoothing effect #Stochastic simulation #Sequential Gaussian simulation #Computer Science, Interdisciplinary Applications #Geosciences, Multidisciplinary |
Tipo |
article original article publishedVersion |