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Modele hierarchiczne w prognozowaniu zmiennych o wysokiej częstotliwości obserwowania w warunkach braku pełnej informacji

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Szmuksta-Zawadzka M., Zawadzki J.
Econometrics. Ekonometria. Advances in Applied Data Analytics
|
2014
|
issue 4(46)
72-84
EN
The paper presents a procedure of application of regular hierarchical models in forecasting missing data in high-frequency time series with cyclical fluctuations. Annual, weekly and daily cycles of seasonal fluctuation have additive character. Separately regular hierarchical models have been built for even length cycles.Theoretical considerations are illustrated with an empirical example.
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