Statistical Inference for Stochastic Processes

A Cramér–von Mises test for a class of mean time dependent CHARN models with application to change-point detection

Joseph Ngatchou-Wandji 1, 2
Marwa Ltaifa 2, 3
1
 
Ehesp, Rennes, France
2
 
Institut Élie Cartan de Lorraine, Vandoeuvre-lès-Nancy Cedex, France
Publication typeJournal Article
Publication date2023-08-23
scimago Q3
SJR0.363
CiteScore1.3
Impact factor0.7
ISSN13870874, 15729311
Statistics and Probability
Abstract
We derive a Cramér–von Mises test for testing a class of time dependent coefficients Coditional Heteroscedastic AutoRegressive Non Linear (CHARN) models. The test statistic is based on the log-likelihood ratio process whose weak convergence in a suitable Fréchet space is studied under the null hypothesis and under the sequence of local alternatives considered. This study makes use of the locally asymptotically normal (LAN) result previously established. Using the Karhunen–Loève expansion of the limiting process of the log-likelihood ratio process, the asymptotic null distribution and the power of the test statistic are accurately approximated. These results are applied to change-point analysis. An empirical study is done for evaluating the performance of the methodology proposed.
Found 

Are you a researcher?

Create a profile to get free access to personal recommendations for colleagues and new articles.
Share
Cite this
GOST | RIS | BibTex
Found error?