wavMRD {wmtsa} | R Documentation |
Let W(j,n) be a discrete
wavelet packet crystal where j is the
decomposition level and n is the oscillation
index. The detail sequence D(j,t)
is formed (essentially) by reconstructing the transform after zeroing out all other crystals
except W(j,n).
The wavMRD
function
calculates the details for a DWT and MODWT in an optimized way.
wavMRD(x, level=NULL, osc=NULL)
x |
an object of class wavTransform . |
level |
an integer (vector) containing the decomposition level(s) corresponding to the
crystal(s) to be decomposed. Default: If the input is of
class wavTransform , then the default is to
return the details at all levels of the transform, i.e., a full multiresolution decomposition. |
osc |
an integer (vector) containing the oscillation indices corresponding to the crystal(s)
to be decomposed. Default: the default values are coordinated with that of the level argument. |
an object of class WaveletMRD
.
Usage: x["D2"] or x["S4"]
Access a subset of wavelet transform details/smooth.
Usage: x["D2"] <- 1:4
Replace an entire wavelet transform details/smooth with explicitly defined coefficients.
Usage: x[["D2"]] or x[[2]]
Returns a vector of wavelet transform detail/smooth coefficients corresponding to the specified crystal.
D4
detail.
Usage: as.matrix(x)
Usage: boxplot(x)
Usage: crystal.names(x)
wavMRD
object.15
.TRUE
, the crystals
are sorted in the display from the most energetic (top) to the
least energetic (bottom) of the specified n.top
crystals.
Default: FALSE
.0.05
.1
.TRUE
, a plot of the sum
of all details/smooth is also plotted. Default: TRUE
.TRUE
, the plot is added to the
current plot layout without a frame ejection. Default: FALSE
.If the transform coefficients were not modified, the original time series will be returned (+/- some numerical noise).
D. B. Percival and A. T. Walden, Wavelet Methods for Time Series Analysis, Cambridge University Press, 2000.
wavMRDSum
, reconstruct
, wavDWT
, wavMODWT
.
## calculate various wavelet transforms of the ## first difference of a linear chirp sequence x <- make.signal("linchirp", n=1024) x.dwt <- wavDWT(x, n.levels = 3) x.modwt <- wavMODWT(x, n.levels = 3) ## calculate the wavelet details for all crystals ## of the DWT and MODWT wavMRD(x.dwt) wavMRD(x.modwt) ## plot the wavelet details for levels 1 and 3 of ## the MODWT plot(wavMRD(x.modwt, level = c(1,3))) ## plot the wavelet details for all levels of the ## MODWT of a linear chirp. plot(wavMRD(x.modwt))