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Effect Of Noise In The Estimation Of Magnitudes With Spatial Dependence: A Spatial Statistics Technique Based On Kriging

机译:噪声对空间依赖性估计的影响:基于Kriging的空间统计技术

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Kriging is a family of linear methods for the estimation of physical quantities with spatial dependence which are optimal in the squared minima sense. To perform the interpolation, kriging considers, in addition to the value and location of the observations, the spatial correlation of the quantity by means of variogram, the random fluctuations of the measured magnitude and the resolution of the measuring devices. The traditional way kriging equations are solved involves the resolution of inverse of great matrices, so that it is normally quite time consuming. Comparing the uncertainty obtained with kriging (for magnitudes with spatial dependence) with standard techniques for uncertainty estimation, we have seen that for the case of regular sampling, the uncertainty estimation can be computed as a convolution.
机译:Kriging是一种用于估计具有空间依赖性的物理量的线性方法系列,其在平方最小值中是最佳的。为了执行插值,除了观察的值和位置之外,克里格汀考虑了通过变速器局的量,测量幅度的随机波动和测量装置的分辨率的空间相关性。传统的Kriging方程被解决涉及解决伟大矩阵的反向,因此通常相当耗时。比较用Kriging(对于具有空间依赖性的大小)获得的不确定性与标准技术进行不确定估计,我们已经看到,对于常规采样的情况,可以计算不确定性估计作为卷积。

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