The consistency for CUSUM estimator of mean change-point model based on association
Min Gao,
Wenzhi Yang,
Xiaoqin Li and
Mei Yao
Communications in Statistics - Theory and Methods, 2025, vol. 54, issue 6, 1836-1867
Abstract:
This article studies the CUSUM estimators of the mean change-point based on the association errors and obtains some important consistency results. For example, the weak and strong convergence rates as well as the limit distribution are obtained for the estimators of the mean change-point and mean parameter. We extend the existing results of mean change points, and give some simulations with Normality and multivariate t distribution errors. As an application, two real data examples are provided to illustrate the analysis of the mean change-point.
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2024.2350605 (text/html)
Access to full text is restricted to subscribers.
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:taf:lstaxx:v:54:y:2025:i:6:p:1836-1867
Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20
DOI: 10.1080/03610926.2024.2350605
Access Statistics for this article
Communications in Statistics - Theory and Methods is currently edited by Debbie Iscoe
More articles in Communications in Statistics - Theory and Methods from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().