Statistical Properties and Uses of the Wavelet Variance Estimator for the Scale Analysis of Time Series
By A. Serroukh, Andrew T. Walden, Donald B. Percival. 2000
155 citations recorded by the source corpus.
Subfields: Computer Vision and Pattern Recognition, Economics and Econometrics, Signal Processing
View Paper: https://www.semanticscholar.org/paper/dc200132aeb3c39bd7d2f2cd0feb64c256df8ee1
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Computer Vision and Pattern Recognition
- Franccois Roueff
- Brandon Whitcher
- Gilles Faÿ
- Eric Moulines
- Murad S. Taqqu
- Ramazan Gencay
- F. Selçuk
- James B. Ramsey
In Economics and Econometrics
- Ramazan Gencay
- Brandon Whitcher
- Franccois Roueff
- F. Selçuk
- Murad S. Taqqu
- Gilles Faÿ
- Eric Moulines
- Patrick M. Crowley
In Signal Processing
Citations in the corpus
- Scaling properties of foreign exchange volatility (2001, background): “[20] showed that the asymptotic variance of ̃(2)X ( j) is given by”
- Estimators of Long-Memory: Fourier versus Wavelets (2008, methodology): “The wavelets present a rich time/frequency representation of the process, which can be more informative than that of the classical Fourier analysis, as discussed in Serroukh et al. (2000), Stoev et al. (2006) and Percival and Walden (2006).”
- Gold, Oil, and Stocks: Dynamic Correlations (2016, unknown): “Plus, Tully and Lucey (2007) show that the U.”