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ssaBSS: Stationary Subspace Analysis

Stationary subspace analysis (SSA) is a blind source separation (BSS) variant where stationary components are separated from non-stationary components. Several SSA methods for multivariate time series are provided here (Flumian et al. (2021); Hara et al. (2010) <doi:10.1007/978-3-642-17537-4_52>) along with functions to simulate time series with time-varying variance and autocovariance (Patilea and Raissi(2014) <doi:10.1080/01621459.2014.884504>).

Version: 0.1.1
Depends: tsBSS (≥ 0.5.3), ICtest (≥ 0.3-4), JADE (≥ 2.0-2), BSSprep, ggplot2
Imports: xts, zoo
Published: 2022-12-01
DOI: 10.32614/CRAN.package.ssaBSS
Author: Markus Matilainen ORCID iD [cre, aut], Lea Flumian [aut], Klaus Nordhausen ORCID iD [aut], Sara Taskinen ORCID iD [aut]
Maintainer: Markus Matilainen <markus.matilainen at outlook.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: no
Materials: ChangeLog
CRAN checks: ssaBSS results

Documentation:

Reference manual: ssaBSS.pdf

Downloads:

Package source: ssaBSS_0.1.1.tar.gz
Windows binaries: r-devel: ssaBSS_0.1.1.zip, r-release: ssaBSS_0.1.1.zip, r-oldrel: ssaBSS_0.1.1.zip
macOS binaries: r-release (arm64): ssaBSS_0.1.1.tgz, r-oldrel (arm64): ssaBSS_0.1.1.tgz, r-release (x86_64): ssaBSS_0.1.1.tgz, r-oldrel (x86_64): ssaBSS_0.1.1.tgz
Old sources: ssaBSS archive

Linking:

Please use the canonical form https://CRAN.R-project.org/package=ssaBSS to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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