Package: smooth 4.1.1.41004

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.pdf |smooth.html
smooth/json (API)
NEWS

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

Peer review:

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

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

On CRAN:

arimaarima-forecastingcesetsexponential-smoothingforecaststate-spacetime-series

13.39 score 89 stars 25 packages 384 scripts 6.3k downloads 5 mentions 50 exports 20 dependencies

Last updated 1 days agofrom:34ecd8d58f. Checks:OK: 7 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 22 2024
R-4.5-win-x86_64OKNov 22 2024
R-4.5-linux-x86_64OKNov 22 2024
R-4.4-win-x86_64NOTENov 22 2024
R-4.4-mac-x86_64OKNov 22 2024
R-4.4-mac-aarch64OKNov 22 2024
R-4.3-win-x86_64NOTENov 22 2024
R-4.3-mac-x86_64OKNov 22 2024
R-4.3-mac-aarch64OKNov 22 2024

Exports:accuracyadamauto.adamauto.cesauto.gumauto.msarimaauto.ssarimacescmaeses_oldgesgumis.adamis.adam.simis.msarimais.msdecomposeis.msdecompose.forecastis.oesis.oesgis.smoothis.smooth.forecastis.smooth.simis.smoothClagsmodelNamemodelTypemsarimamsarima_oldmsdecomposemulticovoesoesgordersplsreapplyreforecastrmultistepsim.cessim.essim.gumsim.oessim.smasim.ssarimasmasma_oldsmoothCombinesowhatssarimaxtable

Dependencies:askpasscurlgenericsgreyboxhttrjsonlitelatticeMASSmimenloptropensslpracmaR6RcppRcppArmadillostatmodsystexregxtablezoo

Augmented Dynamic Adaptive Model

Rendered fromadam.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2024-08-06
Started: 2020-08-03

ces() - Complex Exponential Smoothing

Rendered fromces.Rmdusingknitr::rmarkdownon Nov 22 2024.

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

es() - Exponential Smoothing

Rendered fromes.Rmdusingknitr::rmarkdownon Nov 22 2024.

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

gum() - Generalised Univariate Model

Rendered fromgum.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2022-01-26
Started: 2018-11-30

oes() - occurrence part of iETS model

Rendered fromoes.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-04-14
Started: 2019-03-28

Simulate functions of the package

Rendered fromsimulate.Rmdusingknitr::rmarkdownon Nov 22 2024.

Last update: 2021-02-18
Started: 2016-09-16

sma() - Simple Moving Average

Rendered fromsma.Rmdusingknitr::rmarkdownon Nov 22 2024.

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

smooth: forecasting using state-space models

Rendered fromsmooth.Rmdusingknitr::rmarkdownon Nov 22 2024.

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

ssarima() - State-Space ARIMA

Rendered fromssarima.Rmdusingknitr::rmarkdownon Nov 22 2024.

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
Complex Exponential Smoothing Autoauto.ces
Automatic GUMauto.gum
State Space ARIMAauto.ssarima
Complex Exponential Smoothingces
Centered Moving Averagecma
Exponential Smoothing in SSOE state space modeles es_old
Forecasting time series using smooth functionsforecast forecast.adam forecast.msdecompose forecast.oes forecast.smooth
Generalised Univariate Modelges gum
Smooth classes checkersis.adam is.adam.sim is.msarima is.msdecompose is.msdecompose.forecast is.oes is.oesg is.smooth is.smooth.forecast is.smooth.sim is.smoothC
Multiple Seasonal ARIMAauto.msarima msarima msarima_old
Multiple seasonal classical decompositionmsdecompose
Function returns the multiple steps ahead covariance matrix of forecast errorsmulticov multicov.smooth
Occurrence ETS modeloes
Occurrence ETS, general modeloesg
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 sma_old
Smooth packagesmooth-package smooth
Combination of forecasts of state space modelssmoothCombine
Function returns the ultimate answer to any questionsowhat
State Space ARIMAssarima