aws: 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. <doi:10.18637/jss.v095.i06>, Usage of the package in neuroimaging is illustrated in Polzehl and Tabelow (2019), Magnetic Resonance Brain Imaging, Appendix A, Springer, Use R! Series. <doi:10.1007/978-3-030-29184-6_6>.

Version: 2.5-1
Depends: R (≥ 3.4.0), awsMethods (≥ 1.1-1)
Imports: methods, gsl
Published: 2021-01-11
Author: Joerg Polzehl [aut, cre], Felix Anker [ctb]
Maintainer: Joerg Polzehl <joerg.polzehl at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright: This package is Copyright (C) 2005-2020 Weierstrass Institute for Applied Analysis and Stochastics.
NeedsCompilation: yes
Citation: aws citation info
Materials: README
CRAN checks: aws results


Reference manual: aws.pdf
Vignettes: A very short inroduction into the aws package


Package source: aws_2.5-1.tar.gz
Windows binaries: r-devel:, r-devel-UCRT:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): aws_2.5-1.tgz, r-release (x86_64): aws_2.5-1.tgz, r-oldrel: aws_2.5-1.tgz
Old sources: aws archive

Reverse dependencies:

Reverse imports: BBEST, dti, fmri, GLAD, qMRI


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