Monitoring parameter change for time series models with application to location-Scale heteroscedastic models

Abstract

In this study, we consider an on-line monitoring procedure to detect a parameter change in general time series models, featuring location-scale heteroscedastic time series models and their conditional quantiles. To resolve this statistical process control (SPC) problem, we employ a residual-based cumulative sum (CUSUM) process specially designed to effectively detect both upward and downward changes in the conditional mean, variance, and quantiles of time series. To attain control limits analytically, limit theorems are provided for the proposed CUSUM monitoring process. A simulation study and real data analysis are conducted to illustrate its validity empirically.