maximum level of coefficients to be affected by threshold
verbose
if verbose=TRUE then information is printed to
the screen
value
threshold value (only utilized in manual.thresh)
hard
Boolean value, if hard=F then soft thresholding is used
seed
sets random seed (only utilized in hybrid.thresh)
return.thresh
if return.thresh=TRUE then the vector of
threshold values is returned, otherwise the surviving wavelet
coefficients are returned
Details
An extensive amount of literature has been written on wavelet
shrinkage. The functions here represent the most basic approaches to
the problem of nonparametric function estimation. See the references
for further information.
Value
The default output is a list structure, the same length as was input,
containing only those wavelet coefficients surviving the threshold.
Author(s)
B. Whitcher (some code taken from R. Todd Ogden)
References
Gencay, R., F. Selcuk and B. Whitcher (2001)
An Introduction to Wavelets and Other Filtering Methods in
Finance and Economics,
Academic Press.
Ogden, R. T. (1996)
Essential Wavelets for Statistical Applications and Data
Analysis,
Birkhauser.
Percival, D. B. and A. T. Walden (2000)
Wavelet Methods for Time Series Analysis,
Cambridge University Press.
Vidakovic, B. (1999)
Statistical Modeling by Wavelets,
John Wiley & Sons.