In our research, we introduce the wavelet transform, WT, to establish the regression. Owning to the ability of handling noise signal, we decided to choose WT as the data-preprocessor. Allpying the multi-resolution analysis, MRA, of WT to decompose every factor into different scaled series. After that, we take the reconstructed series to be new regression model.
The proposed method is evaluated via TAIEX¤Îeconomical factors. The result shows that the WT is better explaining the economical factors than the traditional regression model.
| Identifer | oai:union.ndltd.org:NSYSU/oai:NSYSU:etd-0706106-115458 |
| Date | 06 July 2006 |
| Creators | Huang, Jun-Hao |
| Contributors | Jen-Jsung Huang, Chou-Wen Wang, Chingnun Lee |
| Publisher | NSYSU |
| Source Sets | NSYSU Electronic Thesis and Dissertation Archive |
| Language | Cholon |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | http://etd.lib.nsysu.edu.tw/ETD-db/ETD-search/view_etd?URN=etd-0706106-115458 |
| Rights | not_available, Copyright information available at source archive |
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