Sequential monitoring of high‐dimensional time series
本文提出了两种新的多元指数加权移动平均控制图，基于欧氏距离和方差对角矩阵的逆定义的距离，避免了逆协方差矩阵的计算，适用于高维环境，并通过模拟研究比较了其性能。
Abstract In the paper we derive new types of multivariate exponentially weighted moving average (EWMA) control charts which are based on the Euclidean distance and on the distance defined by using the inverse of the diagonal matrix consisting of the variances. The design of the proposed control schemes does not involve the computation of the inverse covariance matrix and, thus, it can be used in the high‐dimensional setting. The distributional properties of the control statistics are obtained and are used in the determination of the new control procedures. Within an extensive simulation study, the new approaches are compared with the multivariate EWMA control charts which are based on the Mahalanobis distance.