# A Combination of Fuzzy Techniques and Chow Test to DetectStructural Breaks in Time Series

A Combination of Fuzzy Techniques and Chow Test to DetectStructural Breaks in Time Series In a series of papers, we suggested a non-statistical method for the detection of structuralbreaks in a time series. It is based on the applications of special fuzzy modeling methods, namelyFuzzy transform (F-transform) and selected methods of Fuzzy Natural Logic (FNL). In this paper, wecombine our method with the principles of the classical Chow test, which is a well-known statisticalmethod for testing the presence of a structural break. The idea is to construct testing statistics similarto that of the Chow test which is formed from components of the first-degree F-transform. Thesecomponents contain an estimation of the average values of the tangents (slopes) of the time seriesover an imprecisely specified time interval. In this paper, we illustrate our method and its statisticaltest on a real-time series and compare it with three classical statistical methods. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Axioms Multidisciplinary Digital Publishing Institute

# A Combination of Fuzzy Techniques and Chow Test to DetectStructural Breaks in Time Series

, Volume 12 (2) – Jan 19, 2023

## A Combination of Fuzzy Techniques and Chow Test to DetectStructural Breaks in Time Series

, Volume 12 (2) – Jan 19, 2023

### Abstract

In a series of papers, we suggested a non-statistical method for the detection of structuralbreaks in a time series. It is based on the applications of special fuzzy modeling methods, namelyFuzzy transform (F-transform) and selected methods of Fuzzy Natural Logic (FNL). In this paper, wecombine our method with the principles of the classical Chow test, which is a well-known statisticalmethod for testing the presence of a structural break. The idea is to construct testing statistics similarto that of the Chow test which is formed from components of the first-degree F-transform. Thesecomponents contain an estimation of the average values of the tangents (slopes) of the time seriesover an imprecisely specified time interval. In this paper, we illustrate our method and its statisticaltest on a real-time series and compare it with three classical statistical methods.

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ISSN
2075-1680
DOI
10.3390/axioms12020103
Publisher site
See Article on Publisher Site

### Abstract

In a series of papers, we suggested a non-statistical method for the detection of structuralbreaks in a time series. It is based on the applications of special fuzzy modeling methods, namelyFuzzy transform (F-transform) and selected methods of Fuzzy Natural Logic (FNL). In this paper, wecombine our method with the principles of the classical Chow test, which is a well-known statisticalmethod for testing the presence of a structural break. The idea is to construct testing statistics similarto that of the Chow test which is formed from components of the first-degree F-transform. Thesecomponents contain an estimation of the average values of the tangents (slopes) of the time seriesover an imprecisely specified time interval. In this paper, we illustrate our method and its statisticaltest on a real-time series and compare it with three classical statistical methods.

### Journal

AxiomsMultidisciplinary Digital Publishing Institute

Published: Jan 19, 2023

Keywords: time series; structural breaks; Chow test; fuzzy transform; F-transform; evaluative linguistic expressions; fuzzy natural logic