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Nonparametric homogeneity criterion for selective formation of an ensemble of time series segments

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Parent Category: 2026

Category: Content №3 2026

Created on 26 June 2026

Last Updated on 26 June 2026

Published on 30 November -0001

Written by Yu. Holovko

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Authors:

Yu. Holovko*, orcid.org/0000-0001-6081-8072, Dnipro University of Technology, Dnipro, Ukraine, e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

* Corresponding author e-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

повний текст / full article

Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu. 2026, (3): 133 - 145

https://doi.org/10.33271/nvngu/2026-3/133

Abstract:

Purpose. Development of a criterion for testing the homogeneity of timeseries segments that are sequentially combined into an ensemble of segments, which constitutes a prerequisite for obtaining statistically significant estimates of the series.

Methodology. The study is based on probabilistic analysis and statistical modelling. A substantial part of the research is devoted to demonstrating the adequacy of the proposed criterion, including its comparison with a wellknown criterion and advantages over it.

Findings. It is shown that when the proposed criterion is applied to assess the homogeneity of an ensemble with a fixed number of segments, it yields results close to those of the well-known Zhang criterion. The advantages of the proposed criterion become evident during the sequential assessment of the possibility of adding segments to the ensemble. In this case, the number of “lost” segments can be reduced several-fold. The scope of the criterion is limited by the fairly wide ranges of parameters that were used in statistical modelling.

Originality. A new criterion for forming an ensemble of homogeneous timeseries segments is developed. The criterion does not require statistical modelling to determine the distribution functions of the test statistic when varying the number of samples in the segments or the number of segments in the ensemble.

Practical value. The use of the proposed criterion can ensure a significant increase in the statistical reliability of estimates of the state of a process represented as a uniformly sampled time series.

Keywords: nonparametric homogeneity test, time series, segment ensemble, random process

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