Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Idris A. Eckley, Guy P. Nason
Title: LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R
Abstract: Locally stationary process representations have recently been proposed and applied to both time series and image analysis applications. This article describes an implementation of the locally stationary two-dimensional wavelet process approach in R. This package permits construction of estimates of spatially localized spectra and localized autocovariance which can be used to characterize structure within images.

Page views:: 4185. Submitted: 2009-11-30. Published: 2011-07-25.
Paper: LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R     Download PDF (Downloads: 4392)
Supplements:
LS2W_1.3.tar.gz: R source package Download (Downloads: 684; 1MB)
v43i03.R: R example code from the paper Download (Downloads: 680; 1KB)
DOI: 10.18637/jss.v043.i03

by
This work is licensed under the licenses
Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.