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aws (version 1.8-0)

Adaptive Weights Smoothing

Description

The package contains R-functions implementing the Propagation-Separation Approach to adaptive smoothing as described in J. Polzehl and V. Spokoiny (2006), Propagation-Separation Approach for Local Likelihood Estimation, Prob. Theory and Rel. Fields, 135(3):335--362. and J. Polzehl and V. Spokoiny (2004) Spatially adaptive regression estimation: Propagation-separation approach, WIAS-Preprint 998.

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Version

Install

install.packages('aws')

Monthly Downloads

637

Version

1.8-0

License

GPL (>= 2)

Maintainer

Joerg Polzehl

Last Published

May 24th, 2012

Functions in aws (1.8-0)

summary-methods

Methods for Function `summary' from package 'base' in Package `aws'

Adaptive weights smoothing for Gaussian data with variance depending on the mean.

Local polynomial smoothing by AWS

Set the number of cores to use for openMP.

Methods for Function `print' from package 'base' in Package `aws'

extract-methods

Methods for Function extract in Package aws

Kernel smoothing on a 1D, 2D or 3D grid

Methods for Function `plot' from package 'graphics' in Package `aws'

Propagation condition for adaptive weights smoothing

Adaptive smoothing by Intersection of Confidence Intervals (ICI)

awssegment-class

Class "awssegment"

Methods for Function `show' in Package `aws'

Compute risks characterizing the quality of smoothing results

ICIsmooth-class

Class "ICIsmooth"

Class "kernsm"

local constant AWS for irregular (1D/2D) design

Adaptive smoothing by Intersection of Confidence Intervals (ICI) using multiple windows

Extract information from an object of class aws

Segmentation by adaptive weights for Gaussian models.

Binning in 1D, 2D or 3D

AWS for local constant models on a grid

Adaptive Weights Smoothing