cvwavelet {CVThresh}R Documentation

Wavelet reconstruction by level-dependent Cross-Validation

Description

This function reconstructs the noise data by level-dependent cross-validation wavelet shrinkage.

Usage

cvwavelet(y=y, ywd=ywd, cv.optlevel, cv.bsize=1, cv.kfold, 
    cv.random=TRUE, cv.tol=0.1^3, cv.maxiter=100,
    impute.vscale="independent", impute.tol=0.1^3, impute.maxiter=100,
    filter.number=10, family="DaubLeAsymm", thresh.type ="soft", ll=3)

Arguments

y observation
ywd DWT object
cv.optlevel thresholding levels
cv.bsize block size of cross-validation
cv.kfold the number of fold of cross-validation
cv.random whether or not random cross-validation scheme should be used. Set cv.random=TRUE for random cross-validation scheme
cv.tol tolerance for cross-validation
cv.maxiter maximum iteration for cross-validation
impute.vscale specifies whether variance is adjusted level-by-level or not. ``level" or ``independent"
impute.tol tolerance for imputation
impute.maxiter maximum iteration for imputation
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

This function performs level-dependent cross-validation wavelet shrinkage.

Value

y observations
yimpute imputed values by provided cross-validation scheme
yc reconstruction by level-dependent cross-validation wavelet shrinkage
cvthresh threshold values by level-dependent cross-validation

See Also

cvtype, cvimpute.by.wavelet, cvwavelet.after.impute.

Examples

data(ipd)
y <- as.numeric(ipd); n <- length(y); nlevel <- log2(n)
ywd <- wd(y)
out <- cvwavelet(y=y, ywd=ywd, cv.optlevel=c(3:(nlevel-1)), 
                     cv.bsize=2, cv.kfold=4)

ts.plot(ts(out$yc, start=1229.98, deltat=0.02, frequency=50),
   main="Level-dependent Cross Validation", xlab = "Seconds", ylab="")

[Package CVThresh version 1.0.5 Index]