Open AccessTime series forecasting using amplitude-frequency analysis of STL components
Author(s) -
D. G. Chkalova
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/2094/3/032019
Subject(s) - interpretability , metric (unit) , amplitude , series (stratigraphy) , computer science , time series , algorithm , harmonic , fourier series , harmonic analysis , fast fourier transform , fourier analysis , quality (philosophy) , software , fourier transform , mathematics , artificial intelligence , machine learning , engineering , acoustics , mathematical analysis , paleontology , philosophy , operations management , physics , epistemology , quantum mechanics , biology , programming language
The problem of economic time series analysis and forecasting using amplitude-frequency analysis of STL decomposition is considered. An amplitude-phase operator was chosen as an apparatus for extraction the series harmonic components, the advantages of which (compared to the Fourier transform) are: calculations speed, result accuracy, simplicity and interpretability of software implementation. The forecast quality was carried out using the MAPE metric. Significantly higher prediction quality was achieved compared to Facebook Prophet forecasting package.