tsBSS

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) <doi:10.1016/j.spl.2015.04.033>; Matilainen, Miettinen, Nordhausen, Oja and Taskinen (2017) <doi:10.17713/ajs.v46i3-4.671>) and supervised dimension reduction problem for multivariate time series (Matilainen, Croux, Nordhausen and Oja (2017) <doi:10.1016/j.ecosta.2017.04.002>). Different functions based on AMUSE and SOBI are also provided for estimating the dimension of the white noise subspace.

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Description file content

Package
tsBSS
Type
Package
Title
Blind Source Separation and Supervised Dimension Reduction for Time Series
Version
0.5.2
Date
2018-10-09
Author
Markus Matilainen, Christophe Croux, Jari Miettinen, Klaus Nordhausen, Hannu Oja, Sara Taskinen, Joni Virta
Maintainer
Markus Matilainen
Depends
ICtest, JADE
Imports
Rcpp (>= 0.11.0), forecast, boot, parallel
LinkingTo
Rcpp, RcppArmadillo
Suggests
stochvol
Description
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.
License
GPL (>= 2)
LazyData
true
NeedsCompilation
yes
Packaged
2018-10-09 17:32:39 UTC; manmat
Repository
CRAN
Date/Publication
2018-10-09 18:20:03 UTC

install.packages('tsBSS')

0.5.2

2 months ago

Markus Matilainen

GPL (>= 2)

Depends on

ICtest, JADE

Imports

Rcpp (>= 0.11.0), forecast, boot, parallel

Suggests

stochvol

Discussions