Retrospective Change-Points Detection for Multidimensional Time Series of Arbitrary Nature: Model-Free Technology Based on the ϵ-Complexity Theory

Author:

Piryatinska Alexandra,Darkhovsky BorisORCID

Abstract

We consider a retrospective change-point detection problem for multidimensional time series of arbitrary nature (in particular, panel data). Change-points are the moments at which the changes in generating mechanism occur. Our method is based on the new theory of ϵ-complexity of individual continuous vector functions and is model-free. We present simulation results confirming the effectiveness of the method.

Publisher

MDPI AG

Subject

General Physics and Astronomy

Reference22 articles.

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2. Non-Parametric Statistical Diagnosis: Problems and Methods;Brodsky,2000

3. Limit Theorems in Change-Point Analysis;Csörgö,1997

4. Change-point detection in panel data

5. Structural breaks in time series

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