legion: Forecasting Using Multivariate Models

Functions implementing multivariate state space models for purposes of time series analysis and forecasting. The focus of the package is on multivariate models, such as Vector Exponential Smoothing, Vector ETS (Error-Trend-Seasonal model) etc. It currently includes Vector Exponential Smoothing (VES, de Silva et al., 2010, <doi:10.1177/1471082X0901000401>), Vector ETS (Svetunkov et al., 2023, <doi:10.1016/j.ejor.2022.04.040>) and simulation function for VES.

Version:	0.2.1
Depends:	R (≥ 3.5.0), greybox (≥ 1.0.4), smooth (≥ 3.1.0)
Imports:	Rcpp (≥ 0.12.3), stats, generics (≥ 0.1.2), graphics, grDevices, Matrix, nloptr, utils, zoo
LinkingTo:	Rcpp, RcppArmadillo (≥ 0.8.100.0.0)
Suggests:	numDeriv, testthat, knitr, rmarkdown, doMC, doParallel, foreach
Published:	2025-02-03
DOI:	10.32614/CRAN.package.legion
Author:	Ivan Svetunkov [aut, cre] (Senior Lecturer, Centre for Marketing Analytics and Forecasting, Lancaster University, UK), Kandrika Fadhlan Pritularga [aut] (Lecturer, Centre for Marketing Analytics and Forecasting, Lancaster University, UK)
Maintainer:	Ivan Svetunkov <ivan at svetunkov.com>
BugReports:	https://github.com/config-i1/legion/issues
License:	LGPL-2.1
URL:	https://github.com/config-i1/legion
NeedsCompilation:	yes
Language:	en-GB
Materials:	README NEWS
In views:	TimeSeries
CRAN checks:	legion results

Documentation:

Reference manual:	legion.pdf
Vignettes:	legion: Forecasting Using Multivariate Models (source, R code) ves() - Vector Exponential Smoothing (source, R code) vets() - Vector ETS (source, R code)

Downloads:

Package source:	legion_0.2.1.tar.gz
Windows binaries:	r-devel: legion_0.2.1.zip, r-release: legion_0.2.1.zip, r-oldrel: legion_0.2.1.zip
macOS binaries:	r-devel (arm64): legion_0.2.1.tgz, r-release (arm64): legion_0.2.1.tgz, r-oldrel (arm64): legion_0.2.1.tgz, r-devel (x86_64): legion_0.2.1.tgz, r-release (x86_64): legion_0.2.1.tgz, r-oldrel (x86_64): legion_0.2.1.tgz
Old sources:	legion archive

Reverse dependencies:

Reverse suggests:

smooth

Linking:

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