cvwavelet.after.impute: Cross-Validation Wavelet Shrinkage after imputation

In CVThresh: Level-Dependent Cross-Validation Thresholding

Cross-Validation Wavelet Shrinkage after imputation

Description

This function performs level-dependent cross-validation wavelet shrinkage given the cross-validation scheme and imputation values.

Usage

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)

Arguments

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

Details

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.

Value

Reconstruction and thresholding values by level-dependent cross-validation

yc	reconstruction
cvthresh	thresholding values by level-dependent cross-validation

See Also

cvwavelet, cvtype, cvimpute.by.wavelet.

Examples

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.

CVThresh documentation built on May 2, 2022, 9:09 a.m.