Statistics Seminar - 10/19/21

Abstract: We propose some new procedures to detect a change point in high-dimensional online data. Theoretical properties of the proposed procedures are explored in the high dimensional setting. More precisely, we derive their average run lengths (ARLs) when there is no change point, and expected detection delays (EDDs) when there is a change point. Accuracy of the theoretical results is confirmed by simulation studies. The practical use of the proposed procedures is demonstrated by real data.