Sequential Detection of Common Change in High-dimensional Data Stream
Statistics Theory
2022-06-24 v1 Statistics Theory
Abstract
After obtaining an accurate approximation for , 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 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.
Cite
@article{arxiv.2206.11727,
title = {Sequential Detection of Common Change in High-dimensional Data Stream},
author = {Yanhong Wu and Wei Biao Wu},
journal= {arXiv preprint arXiv:2206.11727},
year = {2022}
}