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, 2023, <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: |
4.3.1 |
| Depends: |
R (≥ 3.0.2), greybox (≥ 2.0.2) |
| 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: |
2025-10-27 |
| DOI: |
10.32614/CRAN.package.smooth |
| Author: |
Ivan Svetunkov [aut, cre] (Senior Lecturer at Centre for Marketing
Analytics and Forecasting, Lancaster University, UK) |
| Maintainer: |
Ivan Svetunkov <ivan at svetunkov.com> |
| BugReports: |
https://github.com/config-i1/smooth/issues |
| License: |
LGPL-2.1 |
| URL: |
https://github.com/config-i1/smooth |
| NeedsCompilation: |
yes |
| Language: |
en-GB |
| Materials: |
README, NEWS |
| In views: |
TimeSeries |
| CRAN checks: |
smooth results |
Documentation:
| Reference manual: |
smooth.html , smooth.pdf
|
| Vignettes: |
Augmented Dynamic Adaptive Model (source, R code)
ces() - Complex Exponential Smoothing (source, R code)
es() - Exponential Smoothing (source, R code)
gum() - Generalised Univariate Model (source, R code)
oes() - occurrence part of iETS model (source, R code)
Simulate functions of the package (source, R code)
sma() - Simple Moving Average (source, R code)
smooth: forecasting using state-space models (source, R code)
ssarima() - State-Space ARIMA (source, R code)
|
Downloads:
Reverse dependencies:
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