Package aws details

Adaptive Weights Smoothing

We provide a collection of R-functions implementing adaptive smoothing procedures in 1D, 2D and 3D. This includes the Propagation-Separation Approach to adaptive smoothing, the Intersecting Confidence Intervals (ICI), variational approaches and a non-local means filter. The package is described in detail in Polzehl J, Papafitsoros K, Tabelow K (2020). Patch-Wise Adaptive Weights Smoothing in R. Journal of Statistical Software, 95(6), 1-27. , Usage of the package in MR imaging is illustrated in Polzehl and Tabelow (2019), Magnetic Resonance Brain Imaging, Appendix A, Springer, Use R! Series. .

Maintainer: Joerg Polzehl < joerg.polzehl at wias-berlin.de >

Documentation

 
From within R, enter citation('aws')

 

If you have any problems with this package you can open a new issue or check the already existing ones here.

 
  Versions(Pending - no previous version)
 
To install this package, start R and enter:

source("https://neuroconductor.org/neurocLite.R")

# Default Install
neuro_install('aws')

# from GitHub
neuro_install('aws', release = "stable", release_repo = "github")
neuro_install('aws', release = "current", release_repo = "github")

More detailed installation instructions can be found here.

 

Initially submitted on February 3 2020 2:54PM
Last updated on March 31 2021 10:00AM
Package type standard
Source GitHub https://github.com/WIAS-BERLIN/aws GitHub
Neuroconductor GitHub https://github.com/neuroconductor/aws GitHub
DependsR (3.4.0), awsMethods(>=1.1-1)
Importsmethods, gsl
Reverse Importsdti (2.4.1), fmri (2.4), qMRI (2.4)