tsBSS: Blind Source Separation and Supervised Dimension Reduction for
Time Series
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: |
1.0.1 |
| Depends: |
JADE (≥ 2.0-2), ICtest (≥ 0.3-7), BSSprep |
| Imports: |
Rcpp (≥ 0.11.0), ICS (≥ 1.4-2), forecast, boot, parallel, xts, zoo |
| LinkingTo: |
Rcpp, RcppArmadillo |
| Suggests: |
stochvol, MTS, tsbox, dr |
| Published: |
2026-04-02 |
| 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 |
Documentation:
Downloads:
Reverse dependencies:
Linking:
Please use the canonical form
https://CRAN.R-project.org/package=tsBSS
to link to this page.