论文标题
数据驱动的更改点估计器
A Data-driven Change-point Estimator
论文作者
论文摘要
Q加权的cusum及其相应的估计量是众所周知的变更点检测和估计的统计数据。他们很难高度依赖变化的位置。提出了具有数据驱动权重的自适应估计器以克服此问题，并表明相应的自适应更改点测试是有效的。
The q-weighted CUSUM and their corresponding estimator are well known statistics for change-point detection and estimation. They have the difficulty that the performance is highly dependent on the location of the change. An adaptive estimator with data-driven weights is presented to overcome this problem, and it is shown that the corresponding adaptive change-point tests are valid.
