Common Change-Point Estimation and Changed Panel Isolation after Sequential Detection in an Exponential Family

Abstract

After a common change point is detected sequentially in N independent panels with observations following a standard exponential family distribution, a BH-type procedure is proposed to isolate the changed panels based on the asymptotic exponential property of CUSUM processes without change with false discovery rate (FDR) control. The common change point is then estimated based on the change-point estimations from the isolated changed panels. Several typical models based on normal, exponential, and Chi-square distributions for detecting changes in mean, rate, and variance are used for illustration with simulation results. A real example with mean or variance change for Dow Jones 30 stock prices is used for illustration.