New distance measures: The route toward truly non-Gaussian geostatistics
New distance measures: The route toward truly non-Gaussian geostatistics
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新的距离测量：通往真正非高斯地质统计学的道路
DOI：
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发表时间：
1988
期刊：
影响因子：
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通讯作者：
A. Journel
中科院分区：
文献类型：
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作者：
A. Journel
投影或最小误差范数算法不要求距离度量是变差函数。在非高斯情况下，导致误差方差最小化的传统变差函数距离度量没有提供明确的优势。其他距离措施，更outlierresistant比变差函数，提出了满足条件的投影定理。由此产生的最小误差范数提供了与传统上从克里金方差获得的数据配置相同的排名。基于实际数字地形数据的案例研究。
The projection or minimum error norm algorithm does not require that the distance measure be a variogram. In non-Gaussian cases, the traditional variogram distance measure leading to minimization of an error variance offers no definite advantage. Other distance measures, more outlierresistant than the variogram, are proposed which fulfill the condition of the projection theorem. The resulting minimum error norms provide the same data configurations ranking as traditionally obtained from kriging variances. A case study based on actual digital terrain data is presented.