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Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package
Author(s) -
Simon Taylor,
Timothy Park,
Idris A. Eckley
Publication year - 2019
Publication title -
journal of statistical software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 7.636
H-Index - 145
ISSN - 1548-7660
DOI - 10.18637/jss.v090.i11
Subject(s) - multivariate statistics , wavelet , series (stratigraphy) , multivariate analysis , r package , coherence (philosophical gambling strategy) , computer science , suite , mathematics , statistics , algorithm , artificial intelligence , geography , geology , paleontology , archaeology
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.

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