DWTexact {multiwave} | R Documentation |
Exact discrete wavelet decomposition
Description
Computes the discrete wavelet transform of the data using the pyramidal algorithm.
Usage
DWTexact(x, filter)
Arguments
x |
vector of raw data |
filter |
Quadrature mirror filter (also called scaling filter, as returned by the |
Value
dwt |
computable Wavelet coefficients without taking into account the border effect. |
indmaxband |
vector containing the largest index of each
band, i.e. for |
Jmax |
largest available scale index (=length of |
Note
This function was rewritten from an original matlab version by Fay et al. (2009)
Author(s)
S. Achard and I. Gannaz
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.
See Also
Examples
res_filter <- scaling_filter('Daubechies',8);
filter <- res_filter$h
u <- rnorm(2^10,0,1)
x <- vfracdiff(u,d=0.2)
resw <- DWTexact(x,filter)
xwav <- resw$dwt
index <- resw$indmaxband
Jmax <- resw$Jmax
## Wavelet scale 1
ws_1 <- xwav[1:index[1]]
## Wavelet scale 2
ws_2 <- xwav[(index[1]+1):index[2]]
## Wavelet scale 3
ws_3 <- xwav[(index[2]+1):index[3]]
### upto Jmax