Function reference • aws

All functions
`ICIcombined()`	Adaptive smoothing by Intersection of Confidence Intervals (ICI) using multiple windows
`ICIsmooth-class`	Class `"ICIsmooth"`
`ICIsmooth()`	Adaptive smoothing by Intersection of Confidence Intervals (ICI)
`TV_denoising()` `TGV_denoising()` `TV_denoising_colour()` `TGV_denoising_colour()`	TV/TGV denoising of image data
`aws-class`	Class `"aws"`
`aws-package`	Adaptive Weights Smoothing
`aws()`	AWS for local constant models on a grid
`aws.gaussian()`	Adaptive weights smoothing for Gaussian data with variance depending on the mean.
`aws.irreg()`	local constant AWS for irregular (1D/2D) design
`aws.segment()`	Segmentation by adaptive weights for Gaussian models.
`awsLocalSigma()` `awslinsd()` `AFLocalSigma()` `estGlobalSigma()` `estimateSigmaCompl()`	3D variance estimation
`awsdata()`	Extract information from an object of class aws
`awssegment-class`	Class `"awssegment"`
`awstestprop()` `pawstestprop()`	Propagation condition for adaptive weights smoothing
`awsweights()`	Generate weight scheme that would be used in an additional aws step
`binning()`	Binning in 1D, 2D or 3D
`extract(<aws>)` `extract(<awssegment>)` `extract(<ICIsmooth>)` `extract(<kernsm>)`	Methods for Function `extract` in Package aws
`gethani()` `getvofh()` `sofmchi()` `residualVariance()` `residualSpatialCorr()`	Auxiliary functions (for internal use)
`kernsm-class`	Class `"kernsm"`
`kernsm()`	Kernel smoothing on a 1D, 2D or 3D grid
`lpaws()`	Local polynomial smoothing by AWS
`nlmeans()`	NLMeans filter in 1D/2D/3D
`paws()`	Adaptive weigths smoothing using patches
`plot-methods`	Methods for Function `plot' from package 'graphics' in Package `aws'
`print-methods`	Methods for Function `print' from package 'base' in Package `aws'
`qmeasures()`	Quality assessment for image reconstructions.
`risk(<array>)` `risk(<aws>)` `risk(<awssegment>)` `risk(<ICIsmooth>)` `risk(<kernsm>)` `risk(<numeric>)`	Compute risks characterizing the quality of smoothing results
`show-methods`	Methods for Function `show' in Package `aws'
`smooth3D()` `medianFilter3D()` `aws3Dmask()` `aws3Dmaskfull()`	Auxiliary 3D smoothing routines
`smse3ms()` `smse3()`	Adaptive smoothing in orientation space SE(3)
`summary-methods`	Methods for Function `summary' from package 'base' in Package `aws'
`vaws()` `vawscov()`	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.
`vpaws()` `vpawscov2()`	vector valued version of function `paws` with homogeneous covariance structure

Reference

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