Package: smooth 4.5.0.41009

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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manual.pdf |manual.html✨
card.svg |card.png
smooth/json (API)
NEWS

# 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

13.74 score 101 stars 28 packages 482 scripts 2.4k downloads 5 mentions 54 exports 20 dependencies

Last updated from:aecd907d25. Checks:11 NOTE, 2 OK. Indexed: yes.

TargetResultTimeFilesSyslog
linux-devel-arm64NOTE316
linux-devel-x86_64NOTE265
source / vignettesOK397
linux-release-arm64NOTE281
linux-release-x86_64NOTE305
macos-release-arm64NOTE191
macos-release-x86_64NOTE405
macos-oldrel-arm64NOTE165
macos-oldrel-x86_64NOTE356
windows-develNOTE246
windows-releaseNOTE253
windows-oldrelNOTE251
wasm-releaseOK190

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

Dependencies:askpasscurlgenericsgreyboxhttrjsonlitelatticeMASSmimenloptropensslpracmaR6RcppRcppArmadillostatmodsystexregxtablezoo

Augmented Dynamic Adaptive Model

Ivan Svetunkov

Rendered fromadam.Rmdusingknitr::rmarkdownon May 28 2026.

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

ces() - Complex Exponential Smoothing

Ivan Svetunkov

Rendered fromces.Rmdusingknitr::rmarkdownon May 28 2026.

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

es() - Exponential Smoothing

Ivan Svetunkov

Rendered fromes.Rmdusingknitr::rmarkdownon May 28 2026.

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

gum() - Generalised Univariate Model

Ivan Svetunkov

Rendered fromgum.Rmdusingknitr::rmarkdownon May 28 2026.

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

oes() - occurrence part of iETS model

Ivan Svetunkov

Rendered fromoes.Rmdusingknitr::rmarkdownon May 28 2026.

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

om() - ADAM-based occurrence model

Ivan Svetunkov

Rendered fromom.Rmdusingknitr::rmarkdownon May 28 2026.

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

Simulate functions of the package

Ivan Svetunkov

Rendered fromsimulate.Rmdusingknitr::rmarkdownon May 28 2026.

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

sma() - Simple Moving Average

Ivan Svetunkov

Rendered fromsma.Rmdusingknitr::rmarkdownon May 28 2026.

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

smooth: forecasting using state-space models

Ivan Svetunkov

Rendered fromsmooth.Rmdusingknitr::rmarkdownon May 28 2026.

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

ssarima() - State-Space ARIMA

Ivan Svetunkov

Rendered fromssarima.Rmdusingknitr::rmarkdownon May 28 2026.

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.oes 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.oes is.oesg 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 model (legacy implementation)oes_old
Occurrence ETS general modeloesg
Occurrence ETS, general modeloesg_old
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
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