ICIsmooth: Adaptive smoothing by Intersection of Confidence Intervals...

In WIAS-BERLIN/aws: Adaptive Weights Smoothing

Adaptive smoothing by Intersection of Confidence Intervals (ICI)

Description

The function performs adaptive smoothing by Intersection of Confidence Intervals (ICI) as described in Katkovnik et al (2006)

Usage

ICIsmooth(y, hmax, hinc = 1.45, thresh = NULL, kern = "Gaussian", m = 0,
          sigma = NULL, nsector = 1, sector = 1, symmetric = FALSE,
          presmooth = FALSE, unit = c("SD","FWHM"))

Arguments

y	Object of class "array" containing the original (response) data on a grid
hmax	maximum bandwidth
hinc	factor used to increase the bandwidth from scale to scale
thresh	threshold used in tests to determine the best scale
kern	Determines the kernel function. Object of class "character" kernel, can be any of c("Gaussian","Uniform","Triangle","Epanechnicov","Biweight","Triweight"). Defaults to kern="Gaussian".
m	Object of class "integer" vector of length length(dy) determining the order of derivatives specified for the coordinate directios.
sigma	error standard deviation
nsector	number of sectors to use. Positive weights are restricted to the sector selected by sector
sector	Object of class "integer" between 1 and nsector. sector used.
symmetric	Object of class "logical" determines if sectors are symmetric with respect to the origin.
presmooth	Object of class "logical" determines if bandwidths are smoothed for more stable results.
unit	How should the bandwidth be interpreted in case of a Gaussian kernel. For "SD" the bandwidth refers to the standard deviation of the kernel while "FWHM" interprets the banwidth in terms of Full Width Half Maximum of the kernel.

Details

This mainly follows Chapter 6.1 in Katkovnik et al (2006).

Value

An object of class ICIsmooth

Author(s)

Joerg Polzehl [e-mail]

References

J. Polzehl, K. Papafitsoros, K. Tabelow (2020). Patch-Wise Adaptive Weights Smoothing in R, Journal of Statistical Software, 95(6), 1-27. doi:10.18637/jss.v095.i06.

V. Katkovnik, K. Egiazarian and J. Astola, Local Approximation Techniques in Signal And Image Processing, SPIE Society of Photo-Optical Instrumentation Engin., 2006, PM157

See Also

ICIcombined, ICIsmooth-class, kernsm

WIAS-BERLIN/aws documentation built on Sept. 10, 2023, 6:20 p.m.