Forecasting time series using wavelets

被引:25
|
作者
Aminghafari, Mina
机构
[1] Univ Paris 11, Math Lab, UMR Probabil Stat & Modelisat C 8628, F-91405 Orsay, France
[2] Amirkabir Univ Technol, Fac Math, Tehran, Iran
[3] Amirkabir Univ Technol, Stat Res Ctr, Tehran, Iran
[4] Univ Paris 05, Paris, France
关键词
forecasting; non-stationary; time series; wavelets;
D O I
10.1142/S0219691307002002
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
This paper deals with wavelets in time series, focusing on statistical forecasting purposes. Recent approaches involve wavelet decompositions in order to handle non-stationary time series in such context. A method, proposed by Renaud et al.,(11) estimates directly the prediction equation by direct regression of the process on the Haar non-decimated wavelet coefficients depending on its past values. In this paper, this method is studied and extended in various directions. The new variants are used first for stationary data and after for stationary data contaminated by a deterministic trend.
引用
收藏
页码:709 / 724
页数:16
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