Geodesic
Identification of the structure break point for data with changing variance
Mathematica Applicanda, Tome 50 (2022) no. 1, pp. 65-106.

Voir la notice de l'article provenant de la source Annales Societatis Mathematicae Polonae Series

In this paper, we discuss the problem of the structure break point detection for data with changing variance. Considering the limitations and advantages of five well-known techniques, we propose a hybrid algorithm dedicated to the considered problem. The new method enables us to detect break point, even if the data exhibit non-Gaussian characteristics and the small differences between variances in separate segments occur. The efficiency is verified for simulated data from three general classes of distributions, namely platykurtic, leptokurtic and mesokurtic classes represented here by Gaussian, Laplace, Student's t, and generalized Gaussian distributions. The simulation study is supported by real data analysis.
DOI : 10.14708/ma.v50i1.7155
Classification : 60E05, 60G10
Mots-clés : changing variance, structural change point, Monte Carlo simulations, real data analysis 
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Justyna Witulska; Agnieszka Wyłomańska. Identification of the structure break point for data with changing variance. Mathematica Applicanda, Tome 50 (2022) no. 1, pp.  65-106. doi : 10.14708/ma.v50i1.7155. http://geodesic.mathdoc.fr/articles/10.14708/ma.v50i1.7155/

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