smooth: Forecasting Using State Space Models
Functions implementing Single Source of Error state space models for purposes of time series analysis and forecasting.
             The package includes ADAM (Svetunkov, 2021, <https://openforecast.org/adam/>),
             Exponential Smoothing (Hyndman et al., 2008, <doi:10.1007/978-3-540-71918-2>),
             SARIMA (Svetunkov & Boylan, 2019 <doi:10.1080/00207543.2019.1600764>),
             Complex Exponential Smoothing (Svetunkov & Kourentzes, 2018, <doi:10.13140/RG.2.2.24986.29123>),
             Simple Moving Average (Svetunkov & Petropoulos, 2018 <doi:10.1080/00207543.2017.1380326>)
             and several simulation functions. It also allows dealing with intermittent demand based on the
             iETS framework (Svetunkov & Boylan, 2019, <doi:10.13140/RG.2.2.35897.06242>).
| Version: | 
3.2.0 | 
| Depends: | 
R (≥ 3.0.2), greybox (≥ 1.0.7) | 
| Imports: | 
Rcpp (≥ 0.12.3), stats, generics (≥ 0.1.2), graphics, grDevices, pracma, statmod, MASS, nloptr, utils, xtable, zoo | 
| LinkingTo: | 
Rcpp, RcppArmadillo (≥ 0.8.100.0.0) | 
| Suggests: | 
legion, numDeriv, testthat, knitr, rmarkdown, doMC, doParallel, foreach | 
| Published: | 
2023-01-18 | 
| Author: | 
Ivan Svetunkov [aut, cre] (Lecturer at Centre for Marketing Analytics
    and Forecasting, Lancaster University, UK) | 
| Maintainer: | 
Ivan Svetunkov  <ivan at svetunkov.ru> | 
| BugReports: | 
https://github.com/config-i1/smooth/issues | 
| License: | 
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] | 
| URL: | 
https://github.com/config-i1/smooth | 
| NeedsCompilation: | 
yes | 
| Language: | 
en-GB | 
| Materials: | 
README NEWS  | 
| In views: | 
TimeSeries | 
| CRAN checks: | 
smooth results | 
Documentation:
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