如何在空间框架中建模协方差结构:方差函数还是相关函数?

Data Analysis and Applications 4 Pub Date : 2015-03-26 DOI:10.1002/9781119721611.ch10

Giovanni Pistone, G. Vicario

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引用次数: 4

摘要

Kriging的基本模型假设高斯分布具有平稳的均值和平稳的方差。在这种情况下，空间过程的联合分布的特征是共同方差和相关矩阵，或者等价地，共同方差和变异函数矩阵。我们将详细讨论实际使用变差函数作为参数化的选项。

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How to Model the Covariance Structure in a Spatial Framework: Variogram or Correlation Function?

The basic Kriging's model assumes a Gaussian distribution with stationary mean and stationary variance. In such a setting, the joint distribution of the spatial process is characterized by the common variance and the correlation matrix or, equivalently, by the common variance and the variogram matrix. We discuss in in detail the option to actually use the variogram as a parameterization.

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Data Analysis and Applications 4

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