Regime change analysis of interval-valued time series with an application to PM10

Abstract

The aim of this paper is to conduct change point analysis of interval-valued time series employing a regression trees approach. In order to deal with such time series we propose to employ a suitable distance measure that takes into account the underlying structure of interval data. Simulation results pertaining to the behavior of the proposed approach as well as an empirical application on a daily sample of air pollutant are provided, that illustrate the practical usefulness of the proposed method.