Simple change point model in heteroscedastic extremes

Aline Mefleh

Communications in Statistics - Theory and Methods, 2023, vol. 52, issue 20, 7455-7464

Abstract: The framework of heteroscedastic extremes developed by Einmahl et al. (2016) has become an important research area due to its contribution to trend detection. While a previous work of Mefleh et al. (2020) studies some parametric trend models, this article constitutes a small extension to another practical case: the simple change point model where the change point is assumed to be known in time. We first study the model theoretically, estimate the parameter by maximum likelihood method and show its consistency and asymptotic normality. We then associate the proposed model with the discrete log-linear trend model previously developed in Mefleh et al. (2020). We finally verify the results by a simulation and apply the model to real data.

Date: 2023
References: Add references at CitEc
Citations:

Downloads: (external link)
http://hdl.handle.net/10.1080/03610926.2022.2046089 (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:52:y:2023:i:20:p:7455-7464

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/lsta20

DOI: 10.1080/03610926.2022.2046089

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 ().