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 |
| Depends: |
tsBSS (≥ 0.5.3), ICtest (≥ 0.3-4), JADE (≥ 2.0-2), BSSprep, ggplot2 |
| Imports: |
xts, zoo |
| Published: |
2021-04-12 |
| Author: |
Markus Matilainen 
[cre, aut],
Lea Flumian [aut],
Klaus Nordhausen
[aut],
Sara Taskinen
[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:
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