Multi-purpose open-end monitoring procedures for multivariate observations based on the empirical distribution function. (English) Zbl 07786778
Summary: 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.
© 2023 John Wiley & Sons Ltd
© 2023 John Wiley & Sons Ltd
MSC:
| 62Mxx | Inference from stochastic processes |
| 62L99 | Sequential statistical methods |
| 62E20 | Asymptotic distribution theory in statistics |
| 62G10 | Nonparametric hypothesis testing |
Keywords:
asymptotic results; change-point detection; open-end monitoring; sequential testing; theoretical quantile estimationReferences:
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