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A hybrid approach to regime shift detection
In this article, we propose a method for the analysis of regime shifts in frequency data. This method identifies those points in the development of a process for which deviations are most extreme. Based on a statistical model, functions are estimated that describe the process. This description can r...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Scandinavian Society for Person-Oriented Research
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848952/ https://www.ncbi.nlm.nih.gov/pubmed/33569140 http://dx.doi.org/10.17505/jpor.2019.04 |
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author | von Eye, Alexander Wiedermann, Wolfgang von Weber, Stefan |
author_facet | von Eye, Alexander Wiedermann, Wolfgang von Weber, Stefan |
author_sort | von Eye, Alexander |
collection | PubMed |
description | In this article, we propose a method for the analysis of regime shifts in frequency data. This method identifies those points in the development of a process for which deviations are most extreme. Based on a statistical model, functions are estimated that describe the process. This description can represent either the entire series of scores or the series before and after a shift point. The shift point can be either given a priori or estimated from the data. The method is hybrid in that it first uses standard models for the estimation of parameters of the process that is examined and then, in a second step, elements of Configural Frequency Analysis. Uni- and multivariate versions of the method are proposed. In data examples, road traffic data from California and Germany are analyzed before and after particular shift points. Extensions of the proposed method are discussed. |
format | Online Article Text |
id | pubmed-7848952 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Scandinavian Society for Person-Oriented Research |
record_format | MEDLINE/PubMed |
spelling | pubmed-78489522021-02-09 A hybrid approach to regime shift detection von Eye, Alexander Wiedermann, Wolfgang von Weber, Stefan J Pers Oriented Res Articles In this article, we propose a method for the analysis of regime shifts in frequency data. This method identifies those points in the development of a process for which deviations are most extreme. Based on a statistical model, functions are estimated that describe the process. This description can represent either the entire series of scores or the series before and after a shift point. The shift point can be either given a priori or estimated from the data. The method is hybrid in that it first uses standard models for the estimation of parameters of the process that is examined and then, in a second step, elements of Configural Frequency Analysis. Uni- and multivariate versions of the method are proposed. In data examples, road traffic data from California and Germany are analyzed before and after particular shift points. Extensions of the proposed method are discussed. Scandinavian Society for Person-Oriented Research 2019-09-12 /pmc/articles/PMC7848952/ /pubmed/33569140 http://dx.doi.org/10.17505/jpor.2019.04 Text en © Person-Oriented Research https://person-research.org/journal/ Authors of articles published in Journal for Person-Oriented Research retain the copyright of their articles and are free to reproduce and disseminate their work. |
spellingShingle | Articles von Eye, Alexander Wiedermann, Wolfgang von Weber, Stefan A hybrid approach to regime shift detection |
title | A hybrid approach to regime shift detection |
title_full | A hybrid approach to regime shift detection |
title_fullStr | A hybrid approach to regime shift detection |
title_full_unstemmed | A hybrid approach to regime shift detection |
title_short | A hybrid approach to regime shift detection |
title_sort | hybrid approach to regime shift detection |
topic | Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7848952/ https://www.ncbi.nlm.nih.gov/pubmed/33569140 http://dx.doi.org/10.17505/jpor.2019.04 |
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