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Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package

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Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package. / Taylor, Simon Allen Charles; Park, Timothy Alexander; Eckley, Idris Arthur.

In: Journal of Statistical Software, Vol. 90, No. 11, 09.08.2019.

Research output: Contribution to Journal/MagazineJournal articlepeer-review

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Taylor SAC, Park TA, Eckley IA. Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package. Journal of Statistical Software. 2019 Aug 9;90(11). doi: 10.18637/jss.v090.i11

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Bibtex

@article{584048ed9f03461fbdb03f3a12c94d5f,
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 synthesis 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 confidence intervals for the multivariate EWS estimation. A demonstration of the package is presented via both a simulated example and a case study using the EuStockMarkets data from the R data repository.",
author = "Taylor, {Simon Allen Charles} and Park, {Timothy Alexander} and Eckley, {Idris Arthur}",
year = "2019",
month = aug,
day = "9",
doi = "10.18637/jss.v090.i11",
language = "English",
volume = "90",
journal = "Journal of Statistical Software",
issn = "1548-7660",
publisher = "University of California at Los Angeles",
number = "11",

}

RIS

TY - JOUR

T1 - Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package

AU - Taylor, Simon Allen Charles

AU - Park, Timothy Alexander

AU - Eckley, Idris Arthur

PY - 2019/8/9

Y1 - 2019/8/9

N2 - 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 synthesis 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 confidence intervals for the multivariate EWS estimation. A demonstration of the package is presented via both a simulated example and a case study using the EuStockMarkets data from the R data repository.

AB - 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 synthesis 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 confidence intervals for the multivariate EWS estimation. A demonstration of the package is presented via both a simulated example and a case study using the EuStockMarkets data from the R data repository.

U2 - 10.18637/jss.v090.i11

DO - 10.18637/jss.v090.i11

M3 - Journal article

VL - 90

JO - Journal of Statistical Software

JF - Journal of Statistical Software

SN - 1548-7660

IS - 11

ER -