cvwavelet.after.impute | R Documentation |
This function performs level-dependent cross-validation wavelet shrinkage given the cross-validation scheme and imputation values.
cvwavelet.after.impute(y, ywd, yimpute, cv.index, cv.optlevel, cv.tol=0.1^3, cv.maxiter=100, filter.number=10, family="DaubLeAsymm", thresh.type="soft", ll=3)
y |
observation |
ywd |
DWT object |
yimpute |
imputed values according to cross-validation scheme |
cv.index |
test dataset index according to cross-validation scheme |
cv.optlevel |
thresholding levels |
cv.tol |
tolerance for cross-validation |
cv.maxiter |
maximum iteration for cross-validation |
filter.number |
specifies the smoothness of wavelet in the decomposition (argument of WaveThresh) |
family |
specifies the family of wavelets “DaubExPhase" or “DaubLeAsymm" (argument of WaveThresh) |
thresh.type |
specifies the type of thresholding “hard" or “soft" (argument of WaveThresh) |
ll |
specifies the lowest level to be thresholded |
Calculating the threshold values and reconstructing noisy data y, given the index of each testdata, imputed values according to cross-validation scheme and discrete wavelet transform of y.
Reconstruction and thresholding values by level-dependent cross-validation
yc |
reconstruction |
cvthresh |
thresholding values by level-dependent cross-validation |
cvwavelet
, cvtype
, cvimpute.by.wavelet
.
data(ipd) y <- as.numeric(ipd); n <- length(y); nlevel <- log2(n) set.seed(1) cv.index <- cvtype(n=n, cv.bsize=2, cv.kfold=4, cv.random=TRUE)$cv.index yimpute <- cvimpute.by.wavelet(y=y, impute.index=cv.index)$yimpute ywd <- wd(y) #out <- cvwavelet.after.impute(y=y, ywd=ywd, yimpute=yimpute, #cv.index=cv.index, cv.optlevel=c(3:(nlevel-1))) #ts.plot(ts(out$yc, start=1229.98, deltat=0.02, frequency=50), # main="Level-dependent Cross Validation", xlab = "Seconds", ylab="") ##### Specifying thresholding structure # cv.optlevel <- c(3) # Threshold (level 3 to finest level) at the same time. # cv.optlevel <- c(3, 5) # Threshold two groups of resolution levels, # (level 3, 4) and (level 5 to finest level). # cv.optlevel <- c(3,4,5,6,7,8) # Threshold each resolution level 3 to 8.
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