Applying the Qn estimator online

Abstract

Reliable automatic methods are needed for statistical online monitoring of noisy time series. Application of a robust scale estimator allows to use adaptive thresholds for the detection of outliers and level shifts. We propose a fast update algorithm for the Qn estimator and show by simulations that it leads to more powerful tests than other highly robust scale estimators.