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Regression modelGIS / spatial

稳健协同克里金

稳健协同克里金是一种多元地统计学插值方法,它利用两个或多个空间相关变量,在未采样位置联合估计数值,同时应用稳健的变异函数和交叉变异函数估计量,以限制空间异常值或非高斯测量误差的扭曲影响。

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来源

  1. Cressie, N. A. C. (1993). Statistics for Spatial Data (Revised ed.). John Wiley & Sons. Chapter 3 covers robust variogram estimation and co-kriging. ISBN: 978-0471002550
  2. Genton, M. G., & Rousseeuw, P. J. (1995). The Median Absolute Deviation of Spatial Data. Computational Statistics and Data Analysis, 20(4), 385-400. link

如何引用本页

ScholarGate. (2026, June 3). Robust Co-Kriging Spatial Interpolation. ScholarGate. https://scholargate.app/zh/spatial-analysis/robust-co-kriging

Which method?

Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.

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ScholarGateRobust Co-Kriging (Robust Co-Kriging Spatial Interpolation). 于 2026-06-15 检索自 https://scholargate.app/zh/spatial-analysis/robust-co-kriging · 数据集: https://doi.org/10.5281/zenodo.20539026