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Multivariable variogram and its application to the linear model of coregionalization 总被引:1,自引:0,他引:1
In this article, we present the multivariable variogram, which is defined in a way similar to that of the traditional variogram, by the expected value of a distance, squared, in a space withp dimensions. Combined with the linear model of coregionalization, this tool provides a way for finding the elementary variograms that characterize the different spatial scales contained in a set of data withp variables. In the case in which the number of elementary components is less than or equal to the number of variables, it is possible, by means of nonlinear regression of variograms and cross-variograms, to estimate the coregionalization parameters directly in order to obtain the elementary variables themselves, either by cokriging or by direct matrix inversion. This new tool greatly simplifies the procedure proposed by Matheron (1982) and Wackernagel (1985). The search for the elementary variograms is carried out using only one variogram (multivariable), as opposed to thep(p + 1)/2 required by the Matheron approach. Direct estimation of the linear coregionalization model parameters involves the creation of semipositive definite coregionalization matrices of rank 1. 相似文献
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Christian Weiler 《Surveys in Geophysics》1995,16(5-6):671-679
For the purposes of a thesis at the Institute of avalanche and torrent control at the university of agriculture in Vienna a comparison of two avalanche-models, a hydraulic one from Voellmy/Salm/Gubler and a statistical one from Laatsch/Zenke/Dankerl with exemplary exactly known avalanches of Tyrol and Switzerland was started in 1993. The result of this work was that both models failed by the calculation of avalanches with high recurrence intervals (over 300 years). For the calculation of avalanches with recurrence intervals under 300 years the results of both models are regular. The conclusion is that a combination of two models i.e. a hydraulic one improved by statistical calculations will be the best. 相似文献
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