论文标题
使用远程浓度数据检测气体排放源的新型变更点方法
A novel change point approach for the detection of gas emission sources using remotely contained concentration data
论文作者
论文摘要
以遥感气体发射源的示例为动机，我们得出了两个新的变化点程序，用于多元时间序列，与经典变化点文献相比，不需要在时间序列的不同组件中对齐变化。取而代之的是通过功能关系描述了变化点，其中精确的形状取决于未知的感兴趣参数，例如上面示例中气体发射的来源。提出了两种不同类型的测试和描述变化位置的未知参数的相应估计器。我们在错误时间序列的弱假设下得出了两种测试的零渐近学，并在替代方面显示渐近一致性。此外，我们证明了感兴趣参数的相应估计值一致。通过模拟研究和上述遥感示例详细分析了该方法的小样本行为。
Motivated by an example from remote sensing of gas emission sources, we derive two novel change point procedures for multivariate time series where, in contrast to classical change point literature, the changes are not required to be aligned in the different components of the time series. Instead the change points are described by a functional relationship where the precise shape depends on unknown parameters of interest such as the source of the gas emission in the above example. Two different types of tests and the corresponding estimators for the unknown parameters describing the change locations are proposed. We derive the null asymptotics for both tests under weak assumptions on the error time series and show asymptotic consistency under alternatives. Furthermore, we prove consistency for the corresponding estimators of the parameters of interest. The small sample behavior of the methodology is assessed by means of a simulation study and the above remote sensing example analyzed in detail.
