setartree
SETAR-Tree - A Novel and Accurate Tree Algorithm for Global Time Series Forecasting
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) <arXiv:2211.08661v1>. 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.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.2.1 |
rolling linux/jammy R-4.5 | setartree_0.2.1.tar.gz |
182.7 KiB |
0.2.1 |
rolling linux/noble R-4.5 | setartree_0.2.1.tar.gz |
182.7 KiB |
0.2.1 |
rolling source/ R- | setartree_0.2.1.tar.gz |
109.5 KiB |
0.2.1 |
latest linux/jammy R-4.5 | setartree_0.2.1.tar.gz |
182.7 KiB |
0.2.1 |
latest linux/noble R-4.5 | setartree_0.2.1.tar.gz |
182.7 KiB |
0.2.1 |
latest source/ R- | setartree_0.2.1.tar.gz |
109.5 KiB |
0.2.1 |
2026-04-26 source/ R- | setartree_0.2.1.tar.gz |
109.5 KiB |
0.2.1 |
2026-04-23 source/ R- | setartree_0.2.1.tar.gz |
109.5 KiB |
0.2.1 |
2026-04-09 windows/windows R-4.5 | setartree_0.2.1.zip |
186.7 KiB |
0.2.1 |
2025-04-20 source/ R- | setartree_0.2.1.tar.gz |
109.5 KiB |