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tsBSS

Blind Source Separation and Supervised Dimension Reduction for Time Series

Installation

About

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.

Citation tsBSS citation info

Key Metrics

Version 1.0.0
Published 2021-07-10 1021 days ago
Needs compilation? yes
License GPL-2
License GPL-3
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Maintainer

Maintainer

Markus Matilainen

markus.matilainen@outlook.com

Authors

Markus Matilainen

cre / aut

Christophe Croux

aut

Jari Miettinen

aut

Klaus Nordhausen

aut

Hannu Oja

aut

Sara Taskinen

aut

Joni Virta

aut

Material

ChangeLog
Reference manual
Package source

In Views

TimeSeries

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

tsBSS archive

Depends

ICtest ≥ 0.3-2
JADE ≥ 2.0-2
BSSprep

Imports

Rcpp ≥ 0.11.0
forecast
boot
parallel
xts
zoo

Suggests

stochvol
MTS
tsbox
dr

LinkingTo

Rcpp
RcppArmadillo

Reverse Depends

ssaBSS

Reverse Imports

tensorBSS