Abstract
The paper concerns nonparametric sequential procedures for detection of changes in distribution in series of observations to dependent observations. This a partial survey of procedures based on either ranks or empirical distribution functions or empirical characteristic functions when training (historical) sample is available.
The main focus is on independent observations but their extensions to dependent ones are discussed. Theoretical results are accompanied by a simulation study.
The results can be extended some a more general models.