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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>).
Package details |
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Author | Markus Matilainen [cre, aut] (<https://orcid.org/0000-0002-5597-2670>), Lea Flumian [aut], Klaus Nordhausen [aut] (<https://orcid.org/0000-0002-3758-8501>), Sara Taskinen [aut] (<https://orcid.org/0000-0001-9470-7258>) |
Maintainer | Markus Matilainen <markus.matilainen@outlook.com> |
License | GPL (>= 2) |
Version | 0.1.1 |
Package repository | View on CRAN |
Installation |
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