Rssa: A Collection of Methods for Singular Spectrum Analysis

Methods and tools for Singular Spectrum Analysis including decomposition, forecasting and gap-filling for univariate and multivariate time series. General description of the methods with many examples can be found in the book Golyandina (2018, <doi:10.1007/978-3-662-57380-8>). See 'citation("Rssa")' for details.

Version: 1.0.5
Depends: R (≥ 3.1), svd (≥ 0.4), forecast
Imports: lattice, methods
Suggests: testthat (≥ 0.7), RSpectra, PRIMME
Published: 2022-08-22
DOI: 10.32614/CRAN.package.Rssa
Author: Anton Korobeynikov, Alex Shlemov, Konstantin Usevich, Nina Golyandina
Maintainer: Anton Korobeynikov <anton at>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
SystemRequirements: fftw (>=3.2)
Citation: Rssa citation info
In views: TimeSeries
CRAN checks: Rssa results


Reference manual: Rssa.pdf


Package source: Rssa_1.0.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): Rssa_1.0.5.tgz, r-oldrel (arm64): Rssa_1.0.5.tgz, r-release (x86_64): Rssa_1.0.5.tgz, r-oldrel (x86_64): Rssa_1.0.5.tgz
Old sources: Rssa archive

Reverse dependencies:

Reverse imports: msltrend, Rfssa, TrendSLR, VisitorCounts
Reverse suggests: DecomposeR


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