论文标题
检测时空平均函数的相关变化
Detecting relevant changes in the spatiotemporal mean function
论文作者
论文摘要
对于时空过程$ \ {x_j（s，t）| 〜s \ in s〜，〜t \ in t \} _ {j = 1，\ ldots，n} $，其中$ s $表示空间位置集和$ t $ the time域，我们考虑了测试均值序列更改的问题。与大多数文献相反，我们对任意小的变化不感兴趣，而仅对超过给定阈值的变化。提出了渐近分布测试，这不需要估计长期时空协方差结构。特别是，我们考虑一种基于累积总和范式的功能齐全的方法和测试，研究相应测试统计的较大样品特性，并通过仿真研究研究其有限样本属性。
For a spatiotemporal process $\{X_j(s,t) | ~s \in S~,~t \in T \}_{j =1, \ldots , n} $, where $S$ denotes the set of spatial locations and $T$ the time domain, we consider the problem of testing for a change in the sequence of mean functions. In contrast to most of the literature we are not interested in arbitrarily small changes, but only in changes with a norm exceeding a given threshold. Asymptotically distribution free tests are proposed, which do not require the estimation of the long-run spatiotemporal covariance structure. In particular we consider a fully functional approach and a test based on the cumulative sum paradigm, investigate the large sample properties of the corresponding test statistics and study their finite sample properties by means of simulation study.
