Authors: Dette, Holger
Schüler, Theresa
Vetter, Mathias
Title: Multiscale change point detection for dependent data
Language (ISO): en
Abstract: In this paper we study the theoretical properties of the simultaneous multiscale change point estimator (SMUCE) proposed by Frick et al. (2014) in regression models with dependent error processes. Empirical studies show that in this case the change point estimate is inconsistent, but it is not known if alternatives suggested in the literature for correlated data are consistent. We propose a modification of SMUCE scaling the basic statistic by the long run variance of the error process, which is estimated by a difference-type variance estimator calculated from local means from different blocks. For this modification we prove model consistency for physical dependent error processes and illustrate the finite sample performance by means of a simulation study.
Subject Headings: change point detection
physical dependent processes
multiscale methods
Subject Headings (RSWK): Change-point-Problem
Nichtparametrisches Verfahren
Issue Date: 2018
Appears in Collections:Sonderforschungsbereich (SFB) 823

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