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: 1.0.3
Depends: R (≥ 3.1), svd (≥ 0.4), forecast
Imports: lattice, methods
Suggests: testthat (≥ 0.7), RSpectra, PRIMME
Published: 2020-11-19
Author: Anton Korobeynikov, Alex Shlemov, Konstantin Usevich, Nina Golyandina
Maintainer: Anton Korobeynikov <anton at korobeynikov.info>
BugReports: https://github.com/asl/rssa/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/asl/rssa
NeedsCompilation: yes
SystemRequirements: fftw (>=3.2)
Citation: Rssa citation info
In views: TimeSeries
CRAN checks: Rssa results

Downloads:

Reference manual: Rssa.pdf
Package source: Rssa_1.0.3.tar.gz
Windows binaries: r-devel: Rssa_1.0.3.zip, r-release: Rssa_1.0.3.zip, r-oldrel: Rssa_1.0.3.zip
macOS binaries: r-release: Rssa_1.0.3.tgz, r-oldrel: Rssa_1.0.3.tgz
Old sources: Rssa archive

Reverse dependencies:

Reverse imports: msltrend, Rfssa, TrendSLR

Linking:

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