Functions for defining and conducting a time series prediction process including pre(post)processing, decomposition, modelling, prediction and accuracy assessment. The generated models and its yielded prediction errors can be used for benchmarking other time series prediction methods and for creating a demand for the refinement of such methods. For this purpose, benchmark data from prediction competitions may be used.
Package details |
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Author | Rebecca Pontes Salles [aut, cre, cph] (CEFET/RJ), Eduardo Ogasawara [ths] (CEFET/RJ) |
Maintainer | Rebecca Pontes Salles <rebeccapsalles@acm.org> |
License | GPL (>= 2) |
Version | 5.1 |
URL | https://github.com/RebeccaSalles/TSPred/wiki |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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