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aws (version 1.9-4)

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

1.9-4

License

GPL (>= 2)

Maintainer

Joerg Polzehl

Last Published

March 5th, 2014

Functions in aws (1.9-4)

Adaptive smoothing by Intersection of Confidence Intervals (ICI)

Propagation condition for adaptive weights smoothing

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

Segmentation by adaptive weights for Gaussian models.

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

AWS for local constant models on a grid

Compute risks characterizing the quality of smoothing results

Local polynomial smoothing by AWS

Binning in 1D, 2D or 3D

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

Extract information from an object of class aws

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

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

extract-methods

Methods for Function extract in Package aws

summary-methods

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

Methods for Function `show' in Package `aws'

awssegment-class

Class "awssegment"

ICIsmooth-class

Class "ICIsmooth"

Adaptive Weights Smoothing

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

Class "kernsm"