Computes the number of wavelet coefficients at each scale.
compute_nj(n, N)
Arguments
n: sample size.
N: filter length.
Returns
nj: number of coefficients at each scale.
J: Number of scales.
References
G. Fay, E. Moulines, F. Roueff, M. S. Taqqu (2009) Estimators of long-memory: Fourier versus wavelets. Journal of Econometrics, vol. 151, N. 2, pages 159-177.
S. Achard, I. Gannaz (2016) Multivariate wavelet Whittle estimation in long-range dependence. Journal of Time Series Analysis, Vol 37, N. 4, pages 476-512. http://arxiv.org/abs/1412.0391.
S. Achard, I Gannaz (2019) Wavelet-Based and Fourier-Based Multivariate Whittle Estimation: multiwave. Journal of Statistical Software, Vol 89, N. 6, pages 1-31.
Author(s)
S. Achard and I. Gannaz
See Also
DWTexact, scaling_filter
Examples
res_filter <- scaling_filter('Daubechies',8);filter <- res_filter$h
n <-5^10N <- length(filter)compute_nj(n,N)