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 Documentation: Downloads: Reverse dependencies: Linking:Please use the canonical form https://CRAN.R-project.org/package=tsBSS to link to this page.
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