The wavelet coefficients from a multiple wavelet decomposition structure, mwd.object, (e.g. returned from mwd) are packed into a single matrix in that structure. This function extracts the coefficients corresponding to a particular resolution level.
# S3 method for mwd
accessD(mwd, level, ...)A matrix with mwd$filter$npsi rows containing the extracted coefficients.
Multiple wavelet decomposition structure from which you wish to extract the expansion coefficients.
The level that you wish to extract. If the "original" data has mwd$filter$npsi*2^m data points (mwd$filter$npsi being the multiplicity of the multiple wavelets) then there are m possible levels that you could want to access, indexed by 0,1,...,(m-1)
any other arguments
Tim Downie 1995-6
G P Nason
The mwd function produces a multiple wavelet decomposition object .
The need for this function is a consequence of the pyramidal structure of
Mallats algorithm and the memory efficiency gain achieved by storing
the pyramid as a linear matrix.
AccessD obtains information about where the coefficients appear from the
fl.dbase component of mwd,
in particular the array fl.dbase$first.last.d which gives a complete
specification of index numbers and offsets for mwd$D.
Note that this function and accessC only work on objects of class mwd to extract coefficients. You have to use
putD.mwd to insert wavelet coefficients into a mwd object.
See Downie and Silverman, 1998.
accessD.mwd, draw.mwd, mfirst.last, mfilter.select, mwd, mwd.object, plot.mwd, print.mwd, putC.mwd, putD.mwd, summary.mwd, threshold.mwd, wd, wr.mwd
#
# Get the 3rd level of smoothed data from a decomposition
#
data(ipd)
accessD.mwd(mwd(ipd), level=3)
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