Scalable Chi-Square Distance versus Conventional Statistical Distance for Process Monitoring with Uncorrelated Data Variables

Nong Ye, Connie M. Borror, Darshit Parmar

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


Multivariate statistical process control charts are often used for process monitoring to detect out-of-control anomalies. However, multivariate control charts based on conventional statistical distance measures, such as the one used in the Hotelling's T2 control chart, cannot scale up to large amounts of complex process data, e.g. data with a large number of variables and a high rate of data sampling. In our previous work we developed a multivariate statistical process monitoring procedure based on a more scalable chi-square distance measure and tested this procedure for detecting out-of control anomalies - intrusions - in a computer process using computer audit data. The testing results demonstrated the comparable performance of the scalable chi-square procedure to that of Hotelling's T2 control chart. To establish the chi-square procedure as a generic, viable multivariate statistical processing monitoring procedure, we conduct a series of further studies to understand the detection power and limitations of the chi-square procedure for processes with various kinds of data and various types of out-of-control anomalies in addition to the scalability and demonstrated performance of the chi-square procedure for computer intrusion detection. This paper reports on one of these studies that investigates the effectiveness of the scalable chi-square procedure in detecting out-of-control anomalies in processes with uncorrelated data variables, each of which has a normal probability distribution. The results of this study indicate that the chi-square procedure is at least as effective as Hotelling's T2 control chart for monitoring processes with uncorrelated data variables.

Original languageEnglish (US)
Pages (from-to)505-515
Number of pages11
JournalQuality and Reliability Engineering International
Issue number6
StatePublished - Nov 1 2003


  • Chi-square distance
  • Hotelling's T
  • Process monitoring
  • Statistical distance
  • Uncorrelated data

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Management Science and Operations Research


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