  We propose nonparametric open-end sequential testing procedures that can
detect all types of changes in the contemporary distribution function of
possibly multivariate observations. Their asymptotic properties are
theoretically investigated under stationarity and under alternatives to
stationarity. Monte Carlo experiments reveal their good finite-sample behavior
in the case of continuous univariate, bivariate and trivariate observations. A
short data example concludes the work.
