uh: Denoising via top-down Unbalanced Haar

In unbalhaar: Function Estimation via Unbalanced Haar Wavelets

Denoising via top-down 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 top-down Unbalanced Haar decomposition (according to the selection rule criterion), thresholds it with the universal threshold, and performs the inverse Unbalanced Haar transform to yield an estimate of the signal.

Usage

uh(x, criterion = inner.prod.max)

Arguments

x	a vector of the form “signal + iid Gaussian noise”
criterion	a function which takes a vector of length n and returns an integer between 1 and n-1

Value

an estimate of the signal

Author(s)

Piotr Fryzlewicz

References

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

See Also

uh.bu, best.unbal.haar, inner.prod.max, inner.prod.max.p, hard.thresh, reconstr

Examples

x <- c(rep(0, 100), rep(1, 200)) + rnorm(300)
est <- uh(x)

unbalhaar documentation built on April 19, 2022, 5:05 p.m.