Multiscale change point detection for dependent data
Loading...
Date
2018
Journal Title
Journal ISSN
Volume Title
Publisher
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.
Description
Table of contents
Keywords
change point detection, physical dependent processes, multiscale methods