Detection of Multiple Change Points from Clustering Individual Observations

摘要

In the preliminary analysis,also called Stage 1 analysis or retrospective analysis,of statistical process control,one may confront multiple shifts and/or outliers,especially with a large number of observations.This paper addresses the analysis of individual observations,and shows that the X-chart and CUSUM chart may fail to detect the presence of any shifts or outliers when multiple shifts and/or outliers.The algorithm and an effective stopping rule that controls the false detection rate are described.Suggestions are given for reducing masking and for diagnosing the number of shifts or outliers present.