论文标题
在不规则数据区域的集成协方差函数的快速数值近似方法
Rapid Numerical Approximation Method for Integrated Covariance Functions Over Irregular Data Regions
论文作者
论文摘要
在许多实际应用中，空间数据通常是在面积级别（即块数据）上收集的，以及有关变量在点或块中的推论和预测与已观察到的变量不同，通常取决于基础连续空间过程的积分。在本文中，我们描述了一种基于傅立叶变换的方法，该方法通过该方法在不规则数据区域的协方差函数的多个积分可以在数值上以与传统方法相同的准确性近似，但计算费用大大降低。
In many practical applications, spatial data are often collected at areal levels (i.e., block data) and the inferences and predictions about the variable at points or blocks different from those at which it has been observed typically depend on integrals of the underlying continuous spatial process. In this paper we describe a method based on Fourier transform by which multiple integrals of covariance functions over irregular data regions may be numerically approximated with the same level of accuracy to traditional methods, but at a greatly reduced computational expense.
