waveband:Computes Credible Intervals for Bayesian Wavelet Shrinkage
Computes Bayesian wavelet shrinkage credible intervals for nonparametric regression. The method uses cumulants to derive
Bayesian credible intervals for wavelet regression estimates.
The first four cumulants of the posterior distribution of the
estimates are expressed in terms of the observed data and
integer powers of the mother wavelet functions. These powers
are closely approximated by linear combinations of wavelet
scaling functions at an appropriate finer scale. Hence, a
suitable modification of the discrete wavelet transform allows
the posterior cumulants to be found efficiently for any data
set. Johnson transformations then yield the credible intervals
themselves. Barber, S., Nason, G.P. and Silverman, B.W. (2002)
<doi:10.1111/1467-9868.00332>.
