wt {FRESHD} | R Documentation |
This function performs a level J wavelet transform of the input array (1d, 2d, or 3d) using the pyramid algorithm (Mallat 1989).
wt(x, wf = "la8", J = NULL)
x |
a 1, 2, or 3 dimensional data array. The size of each dimension must be dyadic. |
wf |
the type of wavelet family used. See R-package waveslim for options. |
J |
is the level (depth) of the decomposition. For default |
This is a C++/R wrapper function for a C implementation of the discrete wavelet transform by Brandon Whitcher licensed under the BSD 3 license https://cran.r-project.org/web/licenses/BSD_3_clause, see the Waveslim package; Percival and Walden (2000); Gencay, Selcuk and Whitcher (2001).
Given a data array (1d, 2d or 3d) with dyadic sizes this transform is computed efficiently via the pyramid algorithm see Mallat (1989).
... |
An array with dimensions equal to those of |
Adam Lund, Brandon Whitcher
Gencay, R., F. Selcuk and B. Whitcher (2001) An Introduction to Wavelets and Other Filtering Methods in Finance and Economics, Academic Press.
Mallat, S. G. (1989) A theory for multiresolution signal decomposition: the wavelet representation, IEEE Transactions on Pattern Analysis and Machine Intelligence, 11, No. 7, 674-693.
Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
###1d
x <- as.matrix(rnorm(2^3))
range(x - iwt(wt(x)))
###2d
x <- matrix(rnorm(2^(3 + 4)), 2^3, 2^4)
range(x - iwt(wt(x)))
###3d
x <- array(rnorm(2^(3 + 4 + 5)), c(2^3, 2^4, 2^5))
range(x - iwt(wt(x)))