Optimal spatial sampling design in a multivariate framework
Optimal spatial sampling design in a multivariate framework
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DOI：
10.1023/a:1007511923053
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发表时间：
1999-07-01
期刊：
影响因子：
--
通讯作者：
García-Aróstegui, JL
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文献类型：
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作者：
Bueso, MC;Angulo, JM;García-Aróstegui, JL
研究了由相关变量的抽样信息估计多元随机场的空间抽样设计问题。采用基于熵的方法，目标函数被定义为一个线性组合的变量和/或包含在数据中的感兴趣的位置的信息量方面的一个配方分配不同程度的重要性的变量和位置。在多变量高斯情况下，目标函数作为条件协方差矩阵的几何平均值获得。在一些数值示例中示出了改变变量和/或感兴趣的位置的重要性程度的效果。
The problem of spatial sampling design for estimating a multivariate random field from information obtained by sampling related variables is considered. A formulation assigning different degrees of importance to the variables and locations involved is introduced Adopting an entropy-based approach, an objective function is defined as a linear combination in terms of the amount of information on the variables and/or the locations of interest contained in the data. In the multivariate Gaussian case, the objective function is obtained as a geometric mean of conditional covariance matrices. The effect of varying the degrees of importance for the variables and/or the locations of interest is illustrated in some numerical examples.