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Research output: Contribution to Journal/Magazine › Journal article › peer-review
Research output: Contribution to Journal/Magazine › Journal article › peer-review
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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 -