The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.

The following are references to the package. You should also reference the individual methods used, as detailed in the reference section of the help files for each function.

To cite mvLSW in publications use:

Taylor SAC, Park T, Eckley IA (2019). “Multivariate Locally Stationary Wavelet Analysis with the mvLSW R Package.” Journal of Statistical Software, 90(11), 1–19. doi:10.18637/jss.v090.i11.

Taylor S, Park T, Eckley I, Killick R (2022). mvLSW: Multivariate, Locally Stationary Wavelet Process Estimation. R package version 1.2.5, https://CRAN.R-project.org/package=mvLSW.

To get Bibtex entries use: x <- citation("mvLSW"); toBibtex(x)

Corresponding BibTeX entries:

  @Article{,
    title = {Multivariate Locally Stationary Wavelet Analysis with the
      {mvLSW} {R} Package},
    author = {Simon A. C. Taylor and Timothy Park and Idris A. Eckley},
    journal = {Journal of Statistical Software},
    year = {2019},
    volume = {90},
    number = {11},
    pages = {1--19},
    doi = {10.18637/jss.v090.i11},
  }
  @Manual{,
    title = {{mvLSW}: Multivariate, Locally Stationary Wavelet Process
      Estimation},
    author = {Simon Taylor and Tim Park and Idris Eckley and Rebecca
      Killick},
    year = {2022},
    url = {https://CRAN.R-project.org/package=mvLSW},
    note = {R package version 1.2.5},
  }

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.