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setartree
View on CRAN: Click
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Download and install setartree package within the R console
Install from CRAN:
install.packages("setartree")
Install from Github:
library("remotes")
install_github("cran/setartree") Install by package version:
library("remotes")
install_version("setartree", "0.2.1") Attach the package and use:
library("setartree")
Maintained by
Rakshitha Godahewa
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[Scholar Profile | Author Map]
All associated links for this package
First Published: 2023-02-22
Latest Update: 2023-08-24
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.
How to cite:
Rakshitha Godahewa (2023). setartree: SETAR-Tree - A Novel and Accurate Tree Algorithm for Global Time Series Forecasting. R package version 0.2.1, https://cran.r-project.org/web/packages/setartree. Accessed 07 Oct. 2026.
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Complete documentation for setartree
Functions, R codes and Examples using
the setartree R package
Some associated functions: chaotic_logistic_series . forecast.setarforest . forecast.setartree . reexports . setarforest . setartree-package . setartree . web_traffic_test . web_traffic_train .
Some associated R codes: docData.R . find.split.R . forest.R . setartree-package.R . tree.R . utils.R . Full setartree package functions and examples
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