Package: aws 2.5-6

Joerg Polzehl

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 MR imaging is illustrated in Polzehl and Tabelow (2023), Magnetic Resonance Brain Imaging, 2nd Ed. Appendix A, Springer, Use R! Series. <doi:10.1007/978-3-031-38949-8>.

Authors:Joerg Polzehl [aut, cre], Felix Anker [ctb]

aws_2.5-6.tar.gz
aws_2.5-6.tar.gz(r-4.5-noble)aws_2.5-6.tar.gz(r-4.4-noble)
aws_2.5-6.tgz(r-4.4-emscripten)aws_2.5-6.tgz(r-4.3-emscripten)
aws.pdf |aws.html✨
aws/json (API)

# Install 'aws' in R:
install.packages('aws', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Uses libs:
  • openblas– Optimized BLAS
  • openmp– GCC OpenMP (GOMP) support library

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

5.00 score 9 packages 38 scripts 1.1k downloads 3 mentions 47 exports 2 dependencies

Last updated 25 days agofrom:12f22ac737. Checks:OK: 2. Indexed: no.

TargetResultDate
Doc / VignettesOKOct 01 2024
R-4.5-linux-x86_64OKOct 01 2024

Exports:AFLocalSigmaawsaws.gaussianaws.irregaws.segmentaws3Dmaskaws3DmaskfullawsdataawslinsdawsLocalSigmaawstestpropawsweightsbinningestGlobalSigmaestimateSigmaComplextractgethanigetvofhICIcombinedICIsmoothkernsmlpawsmedianFilter3DnlmeanspawspawstestpropplotprintqmeasuresresidualSpatialCorrresidualVarianceriskshowsmooth3Dsmse3smse3mssofmchisummaryTGV_denoisingTGV_denoising_colourTV_denoisingTV_denoising_colourvawsvawscovvpawsvpawscovvpawscov2

Dependencies:awsMethodsgsl

A very short inroduction into the aws package

Rendered fromaws-Example.Rnwusingutils::Sweaveon Oct 01 2024.

Last update: 2024-10-01
Started: 2020-02-19

Readme and manuals

Help Manual

Help pageTopics
Adaptive Weights Smoothingaws-package
Auxiliary functions (for internal use)gethani getvofh residualSpatialCorr residualVariance sofmchi
AWS for local constant models on a gridaws
Class '"aws"'aws-class
Adaptive weights smoothing for Gaussian data with variance depending on the mean.aws.gaussian
local constant AWS for irregular (1D/2D) designaws.irreg
Segmentation by adaptive weights for Gaussian models.aws.segment
Extract information from an object of class awsawsdata
3D variance estimationAFLocalSigma awslinsd awsLocalSigma estGlobalSigma estimateSigmaCompl
Class '"awssegment"'awssegment-class
Propagation condition for adaptive weights smoothingawstestprop pawstestprop
Generate weight scheme that would be used in an additional aws stepawsweights
Binning in 1D, 2D or 3Dbinning
Methods for Function 'extract' in Package 'aws'extract,ANY-method extract,aws-method extract,awssegment-method extract,ICIsmooth-method extract,kernsm-method extract-methods
Adaptive smoothing by Intersection of Confidence Intervals (ICI) using multiple windowsICIcombined
Adaptive smoothing by Intersection of Confidence Intervals (ICI)ICIsmooth
Class '"ICIsmooth"'ICIsmooth-class
Kernel smoothing on a 1D, 2D or 3D gridkernsm
Class '"kernsm"'kernsm-class
Local polynomial smoothing by AWSlpaws
NLMeans filter in 1D/2D/3Dnlmeans
Adaptive weigths smoothing using patchespaws pawsm
Methods for Function `plot' from package 'graphics' in Package `aws'plot,ANY-method plot,aws-method plot,awssegment-method plot,ICIsmooth-method plot,kernsm-method plot-methods
Methods for Function `print' from package 'base' in Package `aws'print,ANY-method print,aws-method print,awssegment-method print,ICIsmooth-method print,kernsm-method print-methods
Quality assessment for image reconstructions.qmeasures
Compute risks characterizing the quality of smoothing resultsrisk,ANY-method risk,array-method risk,aws-method risk,awssegment-method risk,ICIsmooth-method risk,kernsm-method risk,numeric-method risk-methods
Methods for Function `show' in Package `aws'show,ANY-method show,aws-method show,awssegment-method show,ICIsmooth-method show,kernsm-method show-methods
Auxiliary 3D smoothing routinesaws3Dmask aws3Dmaskfull medianFilter3D smooth3D
Adaptive smoothing in orientation space SE(3)smse3 smse3ms
Methods for Function `summary' from package 'base' in Package `aws'summary,ANY-method summary,aws-method summary,awssegment-method summary,ICIsmooth-method summary,kernsm-method summary-methods
TV/TGV denoising of image dataTGV_denoising TGV_denoising_colour TV_denoising TV_denoising_colour
vector valued version of function 'aws' The function implements the propagation separation approach to nonparametric smoothing (formerly introduced as Adaptive weights smoothing) for varying coefficient likelihood models with vector valued response on a 1D, 2D or 3D grid.vaws vawscov
vector valued version of function 'paws' with homogeneous covariance structurevpaws vpawscov vpawscov2