autostsm: Automatic Structural Time Series Models

Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components, plus optionality for structural interpolation, using the Kalman filter. Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models" <doi:10.1093/oxfordhb/9780195398649.013.0006>. Kim, Chang-Jin and Charles R. Nelson (1999) "State-Space Models with Regime Switching: Classical and Gibbs-Sampling Approaches with Applications" <doi:10.7551/mitpress/6444.001.0001><http://econ.korea.ac.kr/~cjkim/>.

Version: 2.0
Depends: R (≥ 3.5.0), data.table (≥ 1.14)
Imports: maxLik (≥ 1.5), forecast (≥ 8.15), lubridate (≥ 1.7), ggplot2 (≥ 3.3), gridExtra (≥ 2.3), strucchange (≥ 1.5), foreach (≥ 1.5), doSNOW (≥ 1.0), parallel (≥ 4.1), lmtest (≥ 0.9), ggrepel (≥ 0.9), progress (≥ 1.2), sandwich (≥ 3.0)
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat
Published: 2021-11-08
Author: Alex Hubbard
Maintainer: Alex Hubbard <hubbard.alex at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation: yes
In views: TimeSeries
CRAN checks: autostsm results

Documentation:

Reference manual: autostsm.pdf
Vignettes: Automatic Structural Time Series Model

Downloads:

Package source: autostsm_2.0.tar.gz
Windows binaries: r-devel: autostsm_2.0.zip, r-devel-UCRT: autostsm_2.0.zip, r-release: autostsm_2.0.zip, r-oldrel: autostsm_1.6.zip
macOS binaries: r-release (arm64): autostsm_2.0.tgz, r-release (x86_64): autostsm_2.0.tgz, r-oldrel: autostsm_1.6.tgz
Old sources: autostsm archive

Linking:

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