A1288
Title: Multivariate control charts based on multiple testing procedures
Authors: Arthur Yeh - Bowling Green State University (United States) [presenting]
Abstract: The multiple testing procedures have garnered some degree of prominence in modern-era statistical applications, especially in genome and genes sequencing research. Multiple testing procedures can be adapted to construct multivariate control charts. The control charts thus developed can not only monitor correlated variables but also provide instantaneous diagnostics of out-of-control parameters when an out-of-control signal is detected, without much further effort. In essence, the multiple testing procedures-based multivariate control charts simultaneously tackle and provide solutions to two major challenges in multivariate control chart developments and applications, monitoring/detection and diagnostics. Furthermore, these types of charts offer potential solutions to problems that have received little or almost no attention in existing literature, e.g., multivariate control charts for monitoring correlated variables of different types. The discussions focus on some recent work, as well as potential future research directions along the same line.
