unbalhaar (version 2.1)

uh.bu: Denoising via bottom-up Unbalanced Haar

Description

Given an input vector of the form ``signal + iid Gaussian noise'', the function estimates the noise level via Median Absolute Deviation, finds the best bottom-up Unbalanced Haar decomposition, thresholds it with the universal threshold, and performs the inverse Unbalanced Haar transform to yield an estimate of the signal.

Usage

uh.bu(x, stretch = length(x))

Arguments

x

a vector of the form ``signal + iid Gaussian noise''

stretch

at each iteration, only the first 1:stretch elements of the current input vector (whose length decreases by one with each iteration) get scanned in the search for the worst-fitting fine-scale Unbalanced Haar wavelet

Value

an estimate of the signal

References

P. Fryzlewicz (2007) ``Unbalanced Haar technique for nonparametric function estimation''. Journal of the American Statistical Association, 102, 1318-1327.

See Also

uh, best.unbal.haar.bu, hard.thresh.bu, reconstr.bu

Examples

# NOT RUN {
x <- c(rep(0, 100), rep(1, 200)) + rnorm(300)
est <- uh.bu(x)
# }