@misc{Hadaś-Dyduch_Monika_Wavelets_2015,
 author={Hadaś-Dyduch, Monika},
 identifier={DOI: 10.15611/me.2015.11.04},
 year={2015},
 rights={Pewne prawa zastrzeżone na rzecz Autorów i Wydawcy},
 publisher={Wydawnictwo Uniwersytetu Ekonomicznego we Wrocławiu},
 description={Mathematical Economics, 2015, Nr 11 (18), s. 43-54},
 language={eng},
 abstract={The aim of this article is to present original application wavelets to the prediction of short-term of time series. The model proposed to predict short-term time series (in particular for predicting macroeconomic indicators) is a model of copyright. The model is based on wavelet analysis, the Haar wavelet, the Daubechies wavelet and adaptive models. The Daubechies wavelets are a family of orthogonal wavelets and are characterized by a maximal number of vanishing moments for some given support. Adaptive models have been appropriately modified by the introduction of a wavelet function and combined into one predictive model. The results obtained from the study results indicate that the authorial model is an effective tool for short-term predictions. The model was applied to predict macroeconomic indicators.},
 title={Wavelets in the prediction of short-time series},
 type={artykuł},
 keywords={wavelets, prediction, Daubechies wavelets, Haar wavelet},
}