On the robust utilization of non-parametric tests for evaluation of combined and monotonic drift

Non-parametric statistical tests are usually adopted to recognize drift phenomena in data series acquired by automatic measuring systems. Sometimes different tests provide different responses with regard to the presence of drift in data sets. In particular, the application of two commonly used statistical tests (i.e. the Wald-Wolfovitz test, also known as the run test, and the Mann-Whitney test, also known as the reverse arrangement test) to data acquired during long-term trials showed that they exhibited different behaviours regarding shift detection. Thus, a deeper examination of previously indicated statistical tests in real measurements appears of interest; more precisely their effectiveness is verified (i) when cyclical and monotonous drift are concurrently present and (ii) various levels of noise are superimposed on the data gathered. Finally, on the basis of the theoretical results obtained, the statistical tests here examined are applied to the same data set in order to validate their capability in on-line drift recognition.