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Computes Credible Intervals for Bayesian Wavelet Shrinkage

Installation

About

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.

Key Metrics

Version 4.7.2
R ≥ 2.0
Published 2022-11-12 539 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks waveband results

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Maintainer

Maintainer

Guy Nason

g.nason@imperial.ac.uk

Authors

Stuart Barber

aut

Guy Nason

cre / ctb

Material

Reference manual
Package source

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

waveband archive

Depends

R ≥ 2.0
wavethresh ≥ 4.6