Multi‐purpose open‐end monitoring procedures for multivariate observations based on the empirical distribution function
提出一种非参数的开放式序列检验方法，能检测多变量观测值分布函数的所有变化，通过蒙特卡洛实验验证了其在连续单变量、双变量和三变量数据中的良好表现。
We propose non‐parametric 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.