Package: smooth
Type: Package
Title: Forecasting Using State Space Models
Version: 4.3.0
Date: 2025-06-30
Authors@R: person("Ivan", "Svetunkov", email = "ivan@svetunkov.com", role = c("aut", "cre"),
                  comment="Senior Lecturer at Centre for Marketing Analytics and Forecasting, Lancaster University, UK")
URL: https://github.com/config-i1/smooth
BugReports: https://github.com/config-i1/smooth/issues
Language: en-GB
Description: 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>).
License: LGPL-2.1
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
VignetteBuilder: knitr
RoxygenNote: 7.3.2
Encoding: UTF-8
ByteCompile: true
NeedsCompilation: yes
Packaged: 2025-07-01 09:44:45 UTC; config
Author: Ivan Svetunkov [aut, cre] (Senior Lecturer at Centre for Marketing
    Analytics and Forecasting, Lancaster University, UK)
Maintainer: Ivan Svetunkov <ivan@svetunkov.com>
Repository: CRAN
Date/Publication: 2025-07-01 10:50:02 UTC
Built: R 4.6.0; aarch64-apple-darwin20; 2025-07-18 07:25:02 UTC; unix
Archs: smooth.so.dSYM
