Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package
By: Researcher
Disclaimer: The provided code links for this paper are external links. Science Nest has no responsibility for the accuracy, legality or content of these links. Also, by downloading this code(s), you agree to comply with the terms of use as set out by the author(s) of the code(s).
| Authors | Simon A. C. Taylor, Timothy Park, Idris A. Eckley |
| Journal/Conference Name | Journal of Statistical Software |
| Paper Category | Other |
| Paper 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. |
| Date of publication | 2019 |
| Code Programming Language | R |
| Comment |
Copyright Researcher 2022