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Change-point methods for multivariate time-series: paired vectorial observations

Publication at Faculty of Mathematics and Physics |
2020

Abstract

We consider paired and two-sample break-detection procedures for vectorial observations and multivariate time series. The new methods involve L2-type criteria based on empirical characteristic functions and are easy to compute regardless of dimension.

We obtain asymptotic results that allow for application of the methods to a wide range of settings involving on-line as well as retrospective circumstances with dependence between the two time series as well as with dependence within each series.