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: Simon A. C. Taylor, Timothy Park, Idris A. Eckley
Title: Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package
Abstract: This paper describes the R package mvLSW. The package contains a suite of tools for the analysis of multivariate locally stationary wavelet (LSW) time series. Key elements include: (i) the simulation of multivariate LSW time series for a given multivariate evolutionary wavelet spectrum (EWS); (ii) estimation of the time-dependent multivariate EWS for a given time series; (iii) estimation of the time-dependent coherence and partial coherence between time series channels; and, (iv) estimation of approximate confidence intervals for multivariate EWS estimates. A demonstration of the package is presented via both a simulated example and a case study with EuStockMarkets from the datasets package.

Page views:: 2003. Submitted: 2016-12-24. Published: 2019-08-09.
Paper: Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package     Download PDF (Downloads: 562)
Supplements:
mvLSW_1.2.3.tar.gz: R source package Download (Downloads: 49; 1MB)
v90i11.R: R replication code Download (Downloads: 65; 3KB)
DOI: 10.18637/jss.v090.i11

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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.