<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The paper presents an analysis of changes in the structure of the average annual discharges, average annual air temperature, and average annual precipitation time series in Slovakia. Three time series with lengths of observation from 1961 to 2006 were analyzed. An introduction to spectral analysis with Fourier analysis (FA) is given. This method is used to determine significant periods of a time series. Later in this article a description of a wavelet transform (WT) is reviewed. This method is able to work with non-stationary time series and detect when significant periods are presented. Subsequently, models for the detection of potential changes in the structure of the time series analyzed were created with the aim of capturing changes in the cyclical components and the multiannual variability of the time series selected for Slovakia. Finally, some of the comparisons of the time series analyzed are discussed. The aim of the paper is to show the advantages of time series analysis using WT compared with FT. The results were processed in the R software environment.</p></abstract>

The paper presents an analysis of changes in the structure of the average annual discharges, average annual air temperature, and average annual precipitation time series in Slovakia. Three time series with lengths of observation from 1961 to 2006 were analyzed. An introduction to spectral analysis with Fourier analysis (FA) is given. This method is used to determine significant periods of a time series. Later in this article a description of a wavelet transform (WT) is reviewed. This method is able to work with non-stationary time series and detect when significant periods are presented. Subsequently, models for the detection of potential changes in the structure of the time series analyzed were created with the aim of capturing changes in the cyclical components and the multiannual variability of the time series selected for Slovakia. Finally, some of the comparisons of the time series analyzed are discussed. The aim of the paper is to show the advantages of time series analysis using WT compared with FT. The results were processed in the R software environment.

Advantages Of A Time Series Analysis Using Wavelet Transform As Compared With A Fourier Analysis

Department of Land and Water Resources Management, Faculty of Civil Engineering, Slovak University of Technology, Radlinského 11, 813 68, Bratislava, Slovak Republic

Slovak Journal of Civil Engineering

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The paper presents an analysis of changes in the structure of the average annual discharges, average annual air temperature, and average annual precipitation...

Advantages Of A Time Series Analysis Using Wavelet Transform As Compared With A Fourier Analysis

Publié en ligne: 10 juil. 2015

Pages: 30 - 36

DOI: https://doi.org/10.1515/sjce-2015-0010

Mots clés
Statistical analysis, Fourier analysis, wavelet transform

© Faculty of Civil Engineering, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Advantages Of A Time Series Analysis Using Wavelet Transform As Compared With A Fourier Analysis

Publié en ligne: 10 juil. 2015

Pages: 30 - 36

DOI: https://doi.org/10.1515/sjce-2015-0010

Mots clésStatistical analysis, Fourier analysis, wavelet transform

© Faculty of Civil Engineering, Slovak University of Technology

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Mots clés
Statistical analysis, Fourier analysis, wavelet transform