Multivariate surveillance is of interest in industrial production as it enables the monitoring of several components. Recently there has been an increased interest also in other areas such as detection of bioterrorism, spatial surveillance and transaction strategies in finance.
Several types of multivariate counterparts to the univariate Shewhart, EWMA and CUSUM methods have been proposed. Here a review of general approaches to multivariate surveillance is given with respect to how suggested methods relate to general statistical inference principles.
Suggestions are made on the special challenges of evaluating multivariate sur-veillance methods.