论文标题
评估空间平稳性并将空间过程分为固定组件
Assessing Spatial Stationarity and Segmenting Spatial Processes into Stationary Components
论文作者
论文摘要
在这项研究中，我们提出了一种新型技术，用于在地统计学中可视化非平稳性，尤其是在面对不规则间隔位置的数据时。我们的方法取决于制定一个统计量，该统计量跟踪指数协方差函数的稳定微能参数，从而使我们能够应对缺乏重复测量的非机构过程的复杂挑战。我们实施了融合的套索技术，以阐明各种决议的非组织模式。为了预测，我们通过Voronoi Tessellations将空间结构域分为固定的子区域。此外，我们根据两个选定的Voronoi子区域之间提出的统计数据的样本平均值设计了一个强大的平稳性测试。通过模拟研究及其应用于科罗拉多州的沉淀数据集的应用，我们的方法的有效性得到了证明。
In this research, we propose a novel technique for visualizing nonstationarity in geostatistics, particularly when confronted with a single realization of data at irregularly spaced locations. Our method hinges on formulating a statistic that tracks a stable microergodic parameter of the exponential covariance function, allowing us to address the intricate challenges of nonstationary processes that lack repeated measurements. We implement the fused lasso technique to elucidate nonstationary patterns at various resolutions. For prediction purposes, we segment the spatial domain into stationary sub-regions via Voronoi tessellations. Additionally, we devise a robust test for stationarity based on contrasting the sample means of our proposed statistics between two selected Voronoi subregions. The effectiveness of our method is demonstrated through simulation studies and its application to a precipitation dataset in Colorado.
