TSPred: Functions for Benchmarking Time Series Prediction (original) (raw)

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.

Version: 5.1.1
Depends: R (≥ 3.5.0)
Imports: forecast, KFAS, stats, MuMIn, wavelets, ModelMetrics, RSNNS, Rlibeemd, e1071, elmNNRcpp, nnet, randomForest, magrittr, plyr, methods, dplyr, keras, tfdatasets
Published: 2025-06-10
DOI: 10.32614/CRAN.package.TSPred
Author: Rebecca Pontes Salles [aut, cre, cph] (CEFET/RJ), Eduardo Ogasawara [ths] (CEFET/RJ)
Maintainer: Rebecca Pontes Salles
BugReports: https://github.com/RebeccaSalles/TSPred/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/RebeccaSalles/TSPred/wiki
NeedsCompilation: no
Citation: TSPred citation info
CRAN checks: TSPred results

Documentation:

Downloads:

Reverse dependencies:

Linking:

Please use the canonical formhttps://CRAN.R-project.org/package=TSPredto link to this page.