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 wias-berlin.de>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
Copyright:	This package is Copyright (C) 2005-2020 Weierstrass Institute for Applied Analysis and Stochastics.
URL:	http://www.wias-berlin.de/people/polzehl/
NeedsCompilation:	yes
Citation:	aws citation info
Materials:	README
CRAN checks:	aws results

Documentation:

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

Downloads:

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

Reverse dependencies:

Reverse imports:

BBEST, dti, fmri, GLAD, LOMAR, qMRI

Linking:

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