论文标题
高维数据流中共同变化的顺序检测
Sequential Detection of Common Change in High-dimensional Data Stream
论文作者
论文摘要
在获得$ arl_0 $的准确近似值之后，我们首先考虑了多元EWMA图表的最佳权重参数设计，该图表可最大程度地减少平均平均延迟检测时间（SADDT）。在获得其$ ARL_0 $和SADDT之后，与移动平均值（MA），CUSUM，CUSUM，广义似然比测试（GLRT）和Shiryayev-Roberts（S-R）图表进行了比较。为了通过稀疏信号检测变化，提出了硬阈值和软阈值EWMA图表。与其他图表（包括自适应技术）的比较表明，应推荐EWMA程序以其稳健的性能和易于设计。
After obtaining an accurate approximation for $ARL_0$, we first consider the optimal design of weight parameter for a multivariate EWMA chart that minimizes the stationary average delay detection time (SADDT). Comparisons with moving average (MA), CUSUM, generalized likelihood ratio test (GLRT), and Shiryayev-Roberts (S-R) charts after obtaining their $ARL_0$ and SADDT's are conducted numerically. To detect the change with sparse signals, hard-threshold and soft-threshold EWMA charts are proposed. Comparisons with other charts including adaptive techniques show that the EWMA procedure should be recommended for its robust performance and easy design.
