Can I read Multivariate Locally Stationary Wavelet Process Analysis with the mvLSW R Package on EtoBox?

Multivariate Locally Stationary Wavelet Process Analysis with the mvLSW R Package by Taylor, Simon A. C.; Park, Timothy; Eckley, Idris A. is a scholarly article available to read on EtoBox.

What is Multivariate Locally Stationary Wavelet Process Analysis with the mvLSW R Package about?

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. This paper has been accepted by the Journal of Statistical Software. Presented code extracts demonstrating the mvLSW package is performed under version 1.2.1.

Author

Taylor, Simon A. C.; Park, Timothy; Eckley, Idris A.

Published

2018

Language

EN