| wt.filter {wavelets} | R Documentation |
Wavelet Transform Filter
Description
Generates a wavelet transform filter.
Usage
wt.filter(filter="la8", modwt=FALSE, level=1)
Arguments
filter |
A character string indicating which wavelet transform filter to compute or a numeric vector of wavelet (high pass) filter coefficients (not scaling (low pass) coefficients). If a numeric vector is supplied, the length must be even. |
modwt |
A logical value indicating whether to compute the maximal overlap discrete wavelet transform filter. |
level |
An integer value indicating the level of the wavelet filter to compute. |
Details
The character strings currently supported are derived from one of four
classes of wavelet transform filters: Daubechies, Least Asymetric,
Best Localized and Coiflet. The prefixes for filters of these classes
are d, la, bl and c,
respectively. Following the prefix, the filter name consists of an
integer indicating length. Supported lengths are as follows:
- Daubechies
2,4,6,8,10,12,14,16,18,20.
- Least Asymetric
8,10,12,14,16,18,20.
- Best Localized
14,18,20.
- Coiflet
6,12,18,24,30.
Thus, to obtain the Daubechies wavelet transform filter of length 4,
the character string "d4" can be passed to
wt.filter.
This naming convention has one exception: the Daubechies wavelet
transform filter of length 2 is denoted by haar instead of
d2.
Value
Returns an object of class wt.filter, which is an S4 object
with slots
L |
An integer representing the length of the wavelet and scaling filters. |
h |
A numeric vector of wavelet filter coefficients. |
g |
A numeric vector of scaling filter coefficients. |
wt.class |
A character string indicating the class of the wavelet
transform filter. Possible values are |
wt.name |
A character string indicating the name of the wavlet
filter as listed in the Details section, above. If the
|
transform |
A character string indicating whether the resulting
wavelet transform object contains DWT or MODWT coefficients. Possible
values are |
Note
The notation h and g for wavelet and scaling
coefficients, respectively, follows Percival and Walden (2000). In
other texts and articles the reverse notation is often adopted.
Author(s)
Eric Aldrich. ealdrich@gmail.com.
References
Percival, D. B. and A. T. Walden (2000) Wavelet Methods for Time Series Analysis, Cambridge University Press.
See Also
Examples
wt.filter("la14")
wt.filter(1:10, modwt=TRUE)