Package: mvLSW 1.2.5

Daniel Grose
mvLSW: Multivariate, Locally Stationary Wavelet Process Estimation
Tools for analysing multivariate time series with wavelets. This includes: simulation of a multivariate locally stationary wavelet (mvLSW) process from a multivariate evolutionary wavelet spectrum (mvEWS); estimation of the mvEWS, local coherence and local partial coherence. See Park, Eckley and Ombao (2014) <doi:10.1109/TSP.2014.2343937> for details.
Authors:
mvLSW_1.2.5.tar.gz
mvLSW_1.2.5.tar.gz(r-4.5-noble)mvLSW_1.2.5.tar.gz(r-4.4-noble)
mvLSW_1.2.5.tgz(r-4.4-emscripten)mvLSW_1.2.5.tgz(r-4.3-emscripten)
mvLSW.pdf |mvLSW.html✨
mvLSW/json (API)
NEWS
# Install 'mvLSW' in R: |
install.packages('mvLSW', repos = 'https://cloud.r-project.org') |
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 3 years agofrom:5b990968cd. Checks:3 OK. Indexed: yes.
Target | Result | Latest binary |
---|---|---|
Doc / Vignettes | OK | Mar 26 2025 |
R-4.5-linux-x86_64 | OK | Mar 26 2025 |
R-4.4-linux-x86_64 | OK | Mar 26 2025 |
Exports:ApxCIas.mvLSWAutoCorrIPcoherenceis.mvLSWmvEWSrmvLSWSpectrum2TransfervarEWS
Dependencies:dotCall64fieldslatticemapsMASSRcppspamviridisLitewavethreshxtszoo
Citation
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}, }
Readme and manuals
Help Manual
Help page | Topics |
---|---|
Evaluate the Approximate Confidence Interval of a mvEWS Estimate | ApxCI |
Multivariate Locally Stationary Wavelet Object | as.mvLSW is.mvLSW |
Wavelet Autocorrelation Inner Product Functions | AutoCorrIP |
Local Wavelet Coherence and Partial Coherence | coherence |
Multivariate Evolutionary Wavelet Spectrum | mvEWS |
Multivariate, Locally Stationary Wavelet Process Estimation | mvLSW |
Plot mvLSW Object | plot.mvLSW |
Sample a Multivariate Locally Stationary Wavelet Process | rmvLSW simulate.mvLSW |
Convert Between mvEWS and Transfer Function Matrices | Spectrum2Transfer |
Print a Summary of mvLSW Object | print.mvLSW summary.mvLSW |
Asymptotic Variance of the mvEWS Estimate | varEWS |