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