Blind Source Separation and Supervised Dimension Reduction for Time Series

Different estimates are provided to solve the blind source separation problem for multivariate time series with stochastic volatility (Matilainen, Nordhausen and Oja (2015) ; Matilainen, Miettinen, Nordhausen, Oja and Taskinen (2017) ) and supervised dimension reduction problem for multivariate time series (Matilainen, Croux, Nordhausen and Oja (2017) ). Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace.


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install.packages("tsBSS")

0.5.2 by Markus Matilainen, 8 months ago


Browse source code at https://github.com/cran/tsBSS


Authors: Markus Matilainen , Christophe Croux , Jari Miettinen , Klaus Nordhausen , Hannu Oja , Sara Taskinen , Joni Virta


Documentation:   PDF Manual  


GPL (>= 2) license


Imports Rcpp, forecast, boot, parallel

Depends on ICtest, JADE

Suggests stochvol

Linking to Rcpp, RcppArmadillo


Imported by tensorBSS.


See at CRAN