The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
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[@]dogado.de.
Different estimators are provided to solve the blind source separation problem for multivariate time series with stochastic volatility and supervised dimension reduction problem for multivariate time series. Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace. The package is fully described in Nordhausen, Matilainen, Miettinen, Virta and Taskinen (2021) <doi:10.18637/jss.v098.i15>.
Version: | 1.0.0 |
Depends: | ICtest (≥ 0.3-2), JADE (≥ 2.0-2), BSSprep |
Imports: | Rcpp (≥ 0.11.0), forecast, boot, parallel, xts, zoo |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | stochvol, MTS, tsbox, dr |
Published: | 2021-07-10 |
DOI: | 10.32614/CRAN.package.tsBSS |
Author: | Markus Matilainen [cre, aut], Christophe Croux [aut], Jari Miettinen [aut], Klaus Nordhausen [aut], Hannu Oja [aut], Sara Taskinen [aut], Joni Virta [aut] |
Maintainer: | Markus Matilainen <markus.matilainen at outlook.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
NeedsCompilation: | yes |
Citation: | tsBSS citation info |
Materials: | ChangeLog |
In views: | TimeSeries |
CRAN checks: | tsBSS results |
Reference manual: | tsBSS.pdf |
Package source: | tsBSS_1.0.0.tar.gz |
Windows binaries: | r-devel: tsBSS_1.0.0.zip, r-release: tsBSS_1.0.0.zip, r-oldrel: tsBSS_1.0.0.zip |
macOS binaries: | r-release (arm64): tsBSS_1.0.0.tgz, r-oldrel (arm64): tsBSS_1.0.0.tgz, r-release (x86_64): tsBSS_1.0.0.tgz, r-oldrel (x86_64): tsBSS_1.0.0.tgz |
Old sources: | tsBSS archive |
Reverse depends: | ssaBSS |
Reverse imports: | tensorBSS |
Please use the canonical form https://CRAN.R-project.org/package=tsBSS to link to this page.
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.
Health stats visible at Monitor.