An illustration of harmonic regression based on the results of the fast Fourier transformation

The well-known methodology of the Fourier analysis is put against the background in the 2nd half of the century parallel to the development of the time-domain approach in the analysis of mainly economical time series. However, from the author's point of view, the former possesses some hidden an...

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Main Author: Bertfai Imre
Format: Article
Language:English
Published: University of Belgrade 2002-01-01
Series:Yugoslav Journal of Operations Research
Subjects:
Online Access:http://www.doiserbia.nb.rs/img/doi/0354-0243/2002/0354-02430202185B.pdf
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spelling doaj-2b39a8239037445291ffa64e653a50892020-11-24T22:45:11ZengUniversity of BelgradeYugoslav Journal of Operations Research0354-02431820-743X2002-01-0112218520210.2298/YJOR0202185BAn illustration of harmonic regression based on the results of the fast Fourier transformationBertfai ImreThe well-known methodology of the Fourier analysis is put against the background in the 2nd half of the century parallel to the development of the time-domain approach in the analysis of mainly economical time series. However, from the author's point of view, the former possesses some hidden analytical advantages which deserve to be re-introduced to the toolbox of analysts. This paper, through several case studies, reports research results for computer algorithm providing a harmonic model for time series. The starting point of the particular method is a harmonic analysis (Fourier-analysis or Lomb-periodogram). The results are optimized in a multifold manner resulting in a model which is easy to handle and able to forecast the underlying data. The results provided are particularly free from limitations characteristic for that methods. Furthermore, the calculated results are easy to interpret and use for further decisions. Nevertheless, the author intends to enhance the procedure in several ways. The method shown seems to be very effective and useful in modeling time series consisting of periodic terms. An additional advantage is the easy interpretation of the obtained parameters. http://www.doiserbia.nb.rs/img/doi/0354-0243/2002/0354-02430202185B.pdfTime seriesforecastingregressionFourier-analysis.
collection DOAJ
language English
format Article
sources DOAJ
author Bertfai Imre
spellingShingle Bertfai Imre
An illustration of harmonic regression based on the results of the fast Fourier transformation
Yugoslav Journal of Operations Research
Time series
forecasting
regression
Fourier-analysis.
author_facet Bertfai Imre
author_sort Bertfai Imre
title An illustration of harmonic regression based on the results of the fast Fourier transformation
title_short An illustration of harmonic regression based on the results of the fast Fourier transformation
title_full An illustration of harmonic regression based on the results of the fast Fourier transformation
title_fullStr An illustration of harmonic regression based on the results of the fast Fourier transformation
title_full_unstemmed An illustration of harmonic regression based on the results of the fast Fourier transformation
title_sort illustration of harmonic regression based on the results of the fast fourier transformation
publisher University of Belgrade
series Yugoslav Journal of Operations Research
issn 0354-0243
1820-743X
publishDate 2002-01-01
description The well-known methodology of the Fourier analysis is put against the background in the 2nd half of the century parallel to the development of the time-domain approach in the analysis of mainly economical time series. However, from the author's point of view, the former possesses some hidden analytical advantages which deserve to be re-introduced to the toolbox of analysts. This paper, through several case studies, reports research results for computer algorithm providing a harmonic model for time series. The starting point of the particular method is a harmonic analysis (Fourier-analysis or Lomb-periodogram). The results are optimized in a multifold manner resulting in a model which is easy to handle and able to forecast the underlying data. The results provided are particularly free from limitations characteristic for that methods. Furthermore, the calculated results are easy to interpret and use for further decisions. Nevertheless, the author intends to enhance the procedure in several ways. The method shown seems to be very effective and useful in modeling time series consisting of periodic terms. An additional advantage is the easy interpretation of the obtained parameters.
topic Time series
forecasting
regression
Fourier-analysis.
url http://www.doiserbia.nb.rs/img/doi/0354-0243/2002/0354-02430202185B.pdf
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