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Editors-in-chief: Bettina Grün, Torsten Hothorn, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R | Eckley | Journal of Statistical Software
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.

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Paper: LS2W: Implementing the Locally Stationary 2D Wavelet Process Approach in R     Download PDF (Downloads: 3942)
Supplements:
LS2W_1.3.tar.gz: R source package Download (Downloads: 641; 1MB)
v43i03.R: R example code from the paper Download (Downloads: 627; 1KB)
DOI: 10.18637/jss.v043.i03

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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.