Adaptive Weights Smoothing

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Documentation for package ‘aws’ version 2.2-1

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aws-package Adaptive Weights Smoothing
aws AWS for local constant models on a grid
aws-class Class '"aws"'
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.
awsdata Extract information from an object of class aws
awssegment-class Class '"awssegment"'
awstestprop 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-method Methods for Function 'extract' in Package 'aws'
extract-methods Methods for Function 'extract' in Package 'aws'
ICIcombined Adaptive smoothing by Intersection of Confidence Intervals (ICI) using multiple windows
ICIsmooth Adaptive smoothing by Intersection of Confidence Intervals (ICI)
ICIsmooth-class Class '"ICIsmooth"'
kernsm Kernel smoothing on a 1D, 2D or 3D grid
kernsm-class Class '"kernsm"'
lpaws Local polynomial smoothing by AWS
nlmeans NLMeans filter in 1D/2D/3D
paws Adaptive weigths smoothing using patches
pawsm Adaptive weigths smoothing using patches
pawstestprop Propagation condition for adaptive weights smoothing
plot-method Methods for Function 'plot' from package 'graphics' in Package 'aws'
plot-methods Methods for Function 'plot' from package 'graphics' in Package 'aws'
print-method Methods for Function 'print' from package 'base' in Package 'aws'
print-methods Methods for Function 'print' from package 'base' in Package 'aws'
qmeasures Quality assessment for image reconstructions.
risk-method Compute risks characterizing the quality of smoothing results
risk-methods Compute risks characterizing the quality of smoothing results
show-method Methods for Function 'show' in Package 'aws'
show-methods Methods for Function 'show' in Package 'aws'
summary-method Methods for Function 'summary' from package 'base' in Package 'aws'
summary-methods Methods for Function 'summary' from package 'base' in Package 'aws'
TGV_denoising TV/TGV denoising of image data
TGV_denoising_colour TV/TGV denoising of image data
TV_denoising TV/TGV denoising of image data
TV_denoising_colour TV/TGV denoising of image data
vaws 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.
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 vector valued version of function 'paws' with homogeneous covariance structure
vpawscov vector valued version of function 'paws' with homogeneous covariance structure