Package: waveband 4.7.4
Guy Nason
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>.
Authors:
waveband_4.7.4.tar.gz
waveband_4.7.4.tar.gz(r-4.5-noble)waveband_4.7.4.tar.gz(r-4.4-noble)
waveband_4.7.4.tgz(r-4.4-emscripten)waveband_4.7.4.tgz(r-4.3-emscripten)
waveband.pdf |waveband.html✨
waveband/json (API)
| # Install 'waveband' in R: |
| install.packages('waveband', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- nmr - Sample nmr data set
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 19 days agofrom:69d2e02c14. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 05 2024 |
| R-4.5-linux-x86_64 | OK | Nov 05 2024 |
Exports:plot.wbpower.sumprint.wbsummary.wbtest.datawave.band
Dependencies:MASSwavethresh
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Sample nmr data set | nmr |
| Plots output from wave.band. | plot.wb |
| Sums of wavelets raised to integer powers | power.sum |
| Print information about a wb object. | print.wb |
| Print information about a wb object. | summary.wb |
| Test functions for wavelet regression and thresholding | test.data |
| Posterior credible intervals for wavelet regression | wave.band |