Package: setartree Title: SETAR-Tree - A Novel and Accurate Tree Algorithm for Global Time Series Forecasting Version: 0.2.1 Authors@R: c( person("Rakshitha", "Godahewa", email = "rakshithagw@gmail.com", role = c("cre", "aut", "cph")), person("Christoph", "Bergmeir", email = "christoph.bergmeir@monash.edu", role = "aut"), person("Daniel", "Schmidt", email = "daniel.schmidt@monash.edu", role = "aut"), person("Geoffrey", "Webb", email = "geoff.webb@monash.edu", role = "ctb")) Maintainer: Rakshitha Godahewa Description: The implementation of a forecasting-specific tree-based model that is in particular suitable for global time series forecasting, as proposed in Godahewa et al. (2022) . The model uses the concept of Self Exciting Threshold Autoregressive (SETAR) models to define the node splits and thus, the model is named SETAR-Tree. The SETAR-Tree uses some time-series-specific splitting and stopping procedures. It trains global pooled regression models in the leaves allowing the models to learn cross-series information. The depth of the tree is controlled by conducting a statistical linearity test as well as measuring the error reduction percentage at each node split. Thus, the SETAR-Tree requires minimal external hyperparameter tuning and provides competitive results under its default configuration. A forest is developed by extending the SETAR-Tree. The SETAR-Forest combines the forecasts provided by a collection of diverse SETAR-Trees during the forecasting process. License: MIT + file LICENSE URL: https://github.com/rakshitha123/setartree BugReports: https://github.com/rakshitha123/setartree/issues Depends: R (>= 3.5.0) Imports: stats, utils, methods, parallel, generics (>= 0.1.2) Suggests: forecast Encoding: UTF-8 LazyData: true Roxygen: list(markdown = TRUE) RoxygenNote: 7.2.3 Repository: https://rakshitha123.r-universe.dev Date/Publication: 2023-08-24 07:49:05 UTC RemoteUrl: https://github.com/rakshitha123/setartree RemoteRef: HEAD RemoteSha: 6fdd5d8bf50f1d0f69d5d575dc80eec903c6a240 RemoteSubdir: setartree NeedsCompilation: no Packaged: 2026-09-16 10:04:39 UTC; root Author: Rakshitha Godahewa [cre, aut, cph], Christoph Bergmeir [aut], Daniel Schmidt [aut], Geoffrey Webb [ctb]