aws-package {aws}R Documentation

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.

Details

Package: aws
Version: 1.6
Date: 2009-04-07
License: GPL (>=2)
Copyright: 2008 Weierstrass Institute for
Applied Analysis and Stochastics.
URL: http://www.wias-berlin.de/project-areas/stat/

Index:

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.
awsdata                 Extract information from an object of class aws
binning                 Binning in 1D, 2D or 3D
lpaws                   Local polynomial smoothing by AWS

Author(s)

Joerg Polzehl <polzehl@wias-berlin.de>

Maintainer: Joerg Polzehl <polzehl@wias-berlin.de>

References

J. Polzehl and V. Spokoiny (2006) Propagation-Separation Approach for Local Likelihood Estimation, Prob. Theory and Rel. Fields 135(3), 335-362.

J. Polzehl and V. Spokoiny (2004) Spatially adaptive regression estimation: Propagation-separation approach, WIAS-Preprint 998.


[Package aws version 1.6-1 Index]