Multi-purpose open-end monitoring procedures for multivariate observations based on the empirical distribution function
Methodology
2022-11-15 v2
Abstract
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.
Cite
@article{arxiv.2201.10311,
title = {Multi-purpose open-end monitoring procedures for multivariate observations based on the empirical distribution function},
author = {Mark Holmes and Ivan Kojadinovic and Alex Verhoijsen},
journal= {arXiv preprint arXiv:2201.10311},
year = {2022}
}
Comments
45 pages, 8 tables, 11 figures