Package: smooth 4.5.0

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>).

Authors:Ivan Svetunkov [aut, cre]

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smooth_4.5.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
smooth/json (API)

# Install 'smooth' in R:
install.packages('smooth', repos = c('https://config-i1.r-universe.dev', 'https://cloud.r-project.org'))

Bug tracker:https://github.com/config-i1/smooth/issues

Uses libs:
  • openblas– Optimized BLAS
  • c++– GNU Standard C++ Library v3

On CRAN:

Conda:

arimaarima-forecastingcesetsexponential-smoothingforecaststate-spacestatespacetime-seriesopenblascpp

13.82 score 101 stars 28 packages 520 scripts 2.7k downloads 5 mentions 50 exports 20 dependencies

Last updated from:ccbd20d9f6. Checks:13 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64OK287
linux-devel-x86_64OK275
source / vignettesOK392
linux-release-arm64OK283
linux-release-x86_64OK276
macos-release-arm64OK228
macos-release-x86_64OK412
macos-oldrel-arm64OK175
macos-oldrel-x86_64OK540
windows-develOK246
windows-releaseOK240
windows-oldrelOK238
wasm-releaseOK217

Exports:accuracyadamauto.adamauto.cesauto.gumauto.msarimaauto.omauto.ssarimacescmaesgumis.adamis.adam.simis.msarimais.msdecomposeis.msdecompose.forecastis.omis.omgis.smoothis.smooth.forecastis.smooth.simis.smoothClagsmodelNamemodelTypemsarimamsdecomposemulticovoesoesgomomgordersplsreapplyreforecastrmultistepsim.cessim.essim.gumsim.oessim.smasim.ssarimasmasmoothCombinesowhatsparmassarimaxtable

Dependencies:askpasscurlgenericsgreyboxhttrjsonlitelatticeMASSmimenloptropensslpracmaR6RcppRcppArmadillostatmodsystexregxtablezoo

om() - ADAM-based occurrence model
The data | om(): ETS occurrence model | om(): ARIMA occurrence model | om(): Regression occurrence model | omg(): the general two-component occurrence model | auto.om(): automatic occurrence type selection | See also | References
Rendered fromom.Rmdusingknitr::rmarkdown

Last update: 2026-05-11
Started: 2026-05-10

oes() - occurrence part of iETS model
The basics | iETS$_F$ | iETS$_O$ | iETS$_I$ | iETS$_D$ | iETS$_G$ | iETS$_A$ | References
Rendered fromoes.Rmdusingknitr::rmarkdown

Last update: 2026-05-10
Started: 2019-03-28

Simulate functions of the package
Exponential Smoothing | SARIMA | Complex Exponential Smoothing | Generalised Univariate Model | Simple Moving Average
Rendered fromsimulate.Rmdusingknitr::rmarkdown

Last update: 2026-01-05
Started: 2016-09-16

Augmented Dynamic Adaptive Model
ADAM ETS | ADAM ARIMA | ADAM ETSX / ARIMAX / ETSX+ARIMA | Auto ADAM
Rendered fromadam.Rmdusingknitr::rmarkdown

Last update: 2026-01-05
Started: 2020-08-03

gum() - Generalised Univariate Model
Rendered fromgum.Rmdusingknitr::rmarkdown

Last update: 2025-03-03
Started: 2018-11-30

ces() - Complex Exponential Smoothing
Rendered fromces.Rmdusingknitr::rmarkdown

Last update: 2025-02-27
Started: 2016-09-16

smooth: forecasting using state-space models
Methods for the class smooth
Rendered fromsmooth.Rmdusingknitr::rmarkdown

Last update: 2024-04-01
Started: 2016-09-16

es() - Exponential Smoothing
Rendered fromes.Rmdusingknitr::rmarkdown

Last update: 2022-05-28
Started: 2016-09-16

sma() - Simple Moving Average
Rendered fromsma.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2016-09-16

ssarima() - State-Space ARIMA
MSARIMA | References
Rendered fromssarima.Rmdusingknitr::rmarkdown

Last update: 2022-01-26
Started: 2016-09-16

Readme and manuals

Help Manual

Help pageTopics
Error measures for an estimated modelaccuracy.smooth accuracy.smooth.forecast
ADAM is Augmented Dynamic Adaptive Modeladam auto.adam simulate.adam sm.adam
Automatic Occurrence Model Selectionauto.om
Complex Exponential Smoothingauto.ces ces
Centered Moving Averagecma
Exponential Smoothing in SSOE state space modeles
Forecasting time series using smooth functionsforecast forecast.adam forecast.msdecompose forecast.om forecast.omg forecast.smooth
Generalised Univariate Modelauto.gum gum
Smooth classes checkersis.adam is.adam.sim is.msarima is.msdecompose is.msdecompose.forecast is.om is.omg is.smooth is.smooth.forecast is.smooth.sim is.smoothC
Multiple Seasonal ARIMAauto.msarima msarima
Multiple seasonal classical decompositionmsdecompose
Function returns the multiple steps ahead covariance matrix of forecast errorsmulticov multicov.smooth
Occurrence ETS modeloes
Occurrence ETS general modeloesg
Occurrence Modelom
General occurrence modelomg
Functions that extract values from the fitted modellags modelName modelType orders
Plots for the fit and statesplot.adam plot.msdecompose plot.smooth
Prediction Likelihood Scorepls pls.smooth
Reapply the model with randomly generated initial parameters and produce forecastsreapply reforecast
Multiple steps ahead forecast errorsrmultistep
Simulate Complex Exponential Smoothingsim.ces
Simulate Exponential Smoothingsim.es
Simulate Generalised Exponential Smoothingsim.gum
Simulate Occurrence Part of ETS modelsim.oes
Simulate Simple Moving Averagesim.sma
Simulate SSARIMAsim.ssarima
Simulate methods for occurrence (om/omg) state-space modelssimulate.om simulate.omg
Simple Moving Averagesma
Smooth packagesmooth-package smooth
Combination of forecasts of state space modelssmoothCombine
Function returns the ultimate answer to any questionsowhat
Sparse ARMA Model in State Space Formsparma
State Space ARIMAauto.ssarima ssarima