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: 3.1.5 Depends: R (≥ 3.5.0) Imports: maxLik (≥ 1.5-2), forecast (≥ 8.15), lubridate (≥ 1.7), ggplot2 (≥ 3.3), gridExtra (≥ 2.3), strucchange (≥ 1.5), foreach (≥ 1.5), doSNOW (≥ 1.0.19), parallel (≥ 4.1.1), lmtest (≥ 0.9-38), ggrepel (≥ 0.9), progress (≥ 1.2), sandwich (≥ 3.0), data.table (≥ 1.15), kalmanfilter (≥ 2.0.1) Suggests: knitr, rmarkdown, testthat Published: 2024-06-05 DOI: 10.32614/CRAN.package.autostsm Author: Alex Hubbard [aut, cre] Maintainer: Alex Hubbard <hubbard.alex at gmail.com> License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] NeedsCompilation: no Materials: README NEWS In views: TimeSeries CRAN checks: autostsm results Documentation: Downloads: Linking:Please use the canonical form https://CRAN.R-project.org/package=autostsm to link to this page.
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