Forecasting Using Multivariate Models R package legion version 0.2.1 CRAN Task View: TimeSeries (https://CRAN.R-project.org/view=TimeSeries) 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. Software 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 Ivan Svetunkov <ivan@svetunkov.com> Comprehensive R Archive Network (CRAN) 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) LGPL-2.1 2025-02-03 application/tgz https://CRAN.R-project.org/package=legion doi:10.32614/CRAN.package.legion en-GB