Package: smooth 4.5.0

Ivan Svetunkov

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✨
DESCRIPTION |NEWS
card.svg |card.png
smooth/json (API)

# Install 'smooth' in R:

install.packages('smooth', repos = c('https://openforecast-org.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:

arima arima-forecasting ces ets exponential-smoothing forecast state-space statespace time-series openblas cpp

11.84 score 101 stars 30 packages 511 scripts 2.7k downloads 5 mentions 50 exports 20 dependencies

Last updated from:7cc63d8630. Checks:12 ERROR, 1 OK. Indexed: yes.

Target	Result	Time
linux-devel-arm64	ERROR	263
linux-devel-x86_64	ERROR	244
source / vignettes	ERROR	377
linux-release-arm64	ERROR	259
linux-release-x86_64	ERROR	228
macos-release-arm64	ERROR	136
macos-release-x86_64	ERROR	340
macos-oldrel-arm64	ERROR	157
macos-oldrel-x86_64	ERROR	351
windows-devel	ERROR	262
windows-release	ERROR	224
windows-oldrel	ERROR	247
wasm-release	OK	178

Exports:accuracy adam auto.adam auto.ces auto.gum auto.msarima auto.om auto.ssarima ces cma es gum is.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 lags modelName modelType msarima msdecompose multicov oes oesg om omg orders pls reapply reforecast rmultistep sim.ces sim.es sim.gum sim.oes sim.sma sim.ssarima sma smoothCombine sowhat sparma ssarima xtable

Dependencies:askpass curl generics greybox httr jsonlite lattice MASS mime nloptr openssl pracma R6 Rcpp RcppArmadillo statmod sys texreg xtable zoo

Vignettes and/or manual for this package failed to build, some documents may be unavailable. Please inspect thebuild logs for more information.

Citation

Development and contributors

Readme and manuals

Help Manual

Help page	Topics
Error measures for an estimated model	accuracy.smooth accuracy.smooth.forecast
ADAM is Augmented Dynamic Adaptive Model	adam auto.adam simulate.adam sm.adam
Automatic Occurrence Model Selection	auto.om
Complex Exponential Smoothing	auto.ces ces
Centered Moving Average	cma
Exponential Smoothing in SSOE state space model	es
Forecasting time series using smooth functions	forecast forecast.adam forecast.msdecompose forecast.om forecast.omg forecast.smooth
Generalised Univariate Model	auto.gum gum
Smooth classes checkers	is.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 ARIMA	auto.msarima msarima
Multiple seasonal classical decomposition	msdecompose
Function returns the multiple steps ahead covariance matrix of forecast errors	multicov multicov.smooth
Occurrence ETS model	oes
Occurrence ETS general model	oesg
Occurrence Model	om
General occurrence model	omg
Functions that extract values from the fitted model	lags modelName modelType orders
Plots for the fit and states	plot.adam plot.msdecompose plot.smooth
Prediction Likelihood Score	pls pls.smooth
Reapply the model with randomly generated initial parameters and produce forecasts	reapply reforecast
Multiple steps ahead forecast errors	rmultistep
Simulate Complex Exponential Smoothing	sim.ces
Simulate Exponential Smoothing	sim.es
Simulate Generalised Exponential Smoothing	sim.gum
Simulate Occurrence Part of ETS model	sim.oes
Simulate Simple Moving Average	sim.sma
Simulate SSARIMA	sim.ssarima
Simulate methods for occurrence (om/omg) state-space models	simulate.om simulate.omg
Simple Moving Average	sma
Smooth package	smooth-package smooth
Combination of forecasts of state space models	smoothCombine
Function returns the ultimate answer to any question	sowhat
Sparse ARMA Model in State Space Form	sparma
State Space ARIMA	auto.ssarima ssarima