A cumulative sum type of method for environmental monitoring

✍ Scribed by Bryan F. J. Manly; Darryl Mackenzie

• Publisher: John Wiley and Sons
• Year: 2000
• Tongue: English
• Weight: 163 KB
• Volume: 11
• Category: Article
• ISSN: 1180-4009
• DOI: 10.1002/(sici)1099-095x(200003/04)11:2<151::aid-env394>3.0.co;2-b

✦ Synopsis

We describe a graphical approach for detecting changes in the distribution of the variable over a number of monitoring sites between two or more sample times, with associated randomization tests. This method was derived from the cumulative sum (CUSUM) method that was developed initially for industrial process control, but our use diers in some fundamental ways. In particular, the standard CUSUM procedure is used to detect changes with time in the mean of a variable at one location, whereas our concern is with detecting changes with time in the distribution of a variable measured at a number of dierent locations. We compare our randomization test for any changes in distribution with the Mann±Kendall test and analysis of covariance in terms of the power for detecting a systematic time trend aecting all sites, with and without serial correlation in time. We also compare these dierent tests in the situation where trend occurs, but it is not the same at all sites, again with and without serial correlation in time. All tests were adversely aected by high serial correlation, so we repeated the comparisons with the CUSUM and analysis of covariance tests modi®ed to take this into account. We conclude that although our randomization test sometimes has less power than the Mann±Kendall test and analysis of covariance for detecting trends, it does have reasonable power and also has the ability to detect other types of change with time. The modi®ed randomization test is very robust to serial correlation.