Automatic model selection for structural time series decomposition into trend, cycle, and seasonal components using the Kalman filter. See Koopman, Siem Jan and Marius Ooms (2012) "Forecasting Economic Time Series Using Unobserved Components Time Series Models <doi:10.1093/oxfordhb/9780195398649.013.0006>.
Version: | 1.2.1 |
Depends: | R (≥ 3.5.0), data.table (≥ 1.13) |
Imports: | Matrix (≥ 1.2), maxLik (≥ 1.4), forecast (≥ 8.13), lubridate (≥ 1.7), tsutils (≥ 0.9), ggplot2 (≥ 3.3), gridExtra (≥ 2.3), strucchange (≥ 1.5), imputeTS (≥ 3.1), foreach (≥ 1.5), doSNOW (≥ 1.0), parallel (≥ 4.0), zoo (≥ 1.8), lmtest (≥ 0.9), tseries (≥ 0.1), ggrepel (≥ 0.9), progress (≥ 1.2) |
LinkingTo: | Rcpp, RcppArmadillo |
Suggests: | knitr, rmarkdown |
Published: | 2021-03-01 |
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 |
Reference manual: | autostsm.pdf |
Vignettes: |
Automatic Structural Time Series Model |
Package source: | autostsm_1.2.1.tar.gz |
Windows binaries: | r-devel: autostsm_1.2.zip, r-release: autostsm_1.2.1.zip, r-oldrel: not available |
macOS binaries: | r-release: autostsm_1.2.tgz, r-oldrel: not available |
Old sources: | autostsm archive |
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