Comment on Wavelet Analysis and scaling properties of time series
| dc.creator | Govindan, R. B. | |
| dc.date | 2006-12-30 | |
| dc.date.accessioned | 2026-07-07T07:38:04Z | |
| dc.date.available | 2026-07-07T07:38:04Z | |
| dc.description | In a recent work Manimaran et al. [Manimaran et al., Phys. Rev. E 72, 046120 (2005)] propose to use multiresolution Daubechies (DB) wavelets to (detrend) remove the low frequency trends and subsequently to quantify the multifractal structure in a given time series. In this comment, by applying DB wavelets to the long range correlated data we show that in the presence of linear trends, the wavelets could not able to distinguish the correlations from trends. As the DB wavelets based detrending will not be able to quantify the correlations masked by trends, its multifractal extension can not always yield a correct estimate of the multifractal spectrum of the given data. | |
| dc.description | pdf only | |
| dc.identifier | https://arxiv.org/abs/physics/0701009 | |
| dc.identifier | http://arxiv.org/abs/physics/0701009 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/120988 | |
| dc.subject | Data Analysis, Statistics and Probability | |
| dc.subject | Computational Physics | |
| dc.title | Comment on Wavelet Analysis and scaling properties of time series | |
| dc.type | text |