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: 1.0.0
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
Author: Markus Matilainen ORCID iD [cre, aut], Christophe Croux [aut], Jari Miettinen ORCID iD [aut], Klaus Nordhausen ORCID iD [aut], Hannu Oja [aut], Sara Taskinen ORCID iD [aut], Joni Virta ORCID iD [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:

Reference manual: tsBSS.pdf

Downloads:

Package source: tsBSS_1.0.0.tar.gz
Windows binaries: r-devel: tsBSS_1.0.0.zip, r-devel-UCRT: 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-release (x86_64): tsBSS_1.0.0.tgz, r-oldrel: tsBSS_1.0.0.tgz
Old sources: tsBSS archive

Reverse dependencies:

Reverse depends: ssaBSS
Reverse imports: tensorBSS

Linking:

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