artificial.levels {liftLRD} | R Documentation |
This function splits the coefficients into levels according to either (i) increasing quantiles of the removed interval lengths or (ii) dyadic splitting relative to a fixed lowest scale
artificial.levels(y, rem, time, tail = TRUE, type = 1)
y |
a vector of the removed interval lengths (in the order of removelist). |
rem |
vector of indices of the removed points (from the output of the forward transform). |
time |
vector of observed times for the decomposed signal. |
tail |
a boolean variable indicating whether coarse levels with a small number of detail coefficients (less than 10 coefficients) should be combined. |
type |
an integer indicating which type of artificial levels to compute. If |
The function computes the so-called artificial levels of a set of removed integrals and corresponding detail coefficients, to mimic the dyadic level splitting in a classical
wavelet framework. Details on the "usual" quantile-based splitting can be found in artlev
. If type==2
or type==3
, the artificial levels are
defined by intervals of the form [a0 2^j,a0 2^(j-1) ) as described in Jansen et al. (2009), with a0 = 0.5 for type==2
and set to the minimum sampling interval for
type==3
. The amalgamation of coarser artificial levels prevents variable energies at coarser scales affecting the predicted relationship between the wavelet scales
and their corresponding energies.
p |
a list of the grouped indices of removelist (in decreasing group size) indicating thresholding groups. |
Matt Nunes, Marina Knight
Jansen, M, Nason, G. P. and Silverman, B. W. (2009) Multiscale methods for data on graphs and irregular multidimensional situations. J. Roy. Stat. Soc. B 71, Part 1, 97–125.
#create test signal data # library(adlift) x<-runif(100) y<-make.signal2("blocks",x=x) # #perform forward transform... # out<-fwtnp(x,y,LocalPred=AdaptNeigh,neighbours=2) # al<-artificial.levels(out$lengthsremove,out$removelist, x, type = 1) # # # the indices of removelist split into levels: al #