A new tree-based ensemble model that is called tree-based moving average (TBMA) is provided for time series forecasting problems. The TBMA model provides point and probabilistic forecasts and uses both of the tree-based ensemble and MA approaches to consider predictors and time series components. With the use of the tree-based ensemble and MA approaches, the TBMA model can handle a large number of numerical and categorical predictors without sacrificing the accuracy and capture autocorrelation between time series observations.
Package details |
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Author | Burakhan Sel [aut, cre], Mustafa Gokce Baydogan [aut] |
Maintainer | Burakhan Sel <burakhan.sel@boun.edu.tr> |
License | GPL (>= 2) |
Version | 0.1.0 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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