DESCRIPTION

Package: TSPred
Type: Package
Title: Functions for Benchmarking Time Series Prediction
Version: 5.1
Date: 2021-01-14
Authors@R: c(person(c("Rebecca", "Pontes"),"Salles", role = c("aut", "cre","cph"),email = "rebeccapsalles@acm.org", comment = "CEFET/RJ"),
			 person("Eduardo","Ogasawara", role = c("ths"),email = "eogasawara@ieee.org", comment = "CEFET/RJ"))
Author: Rebecca Pontes Salles [aut, cre, cph] (CEFET/RJ), Eduardo Ogasawara [ths] (CEFET/RJ)
Maintainer: Rebecca Pontes Salles <rebeccapsalles@acm.org>
Description: 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.
Depends: R (>= 3.5.0)
Imports: forecast, KFAS, stats, MuMIn, EMD, wavelets, vars,
        ModelMetrics, RSNNS, Rlibeemd, e1071, elmNNRcpp, nnet,
        randomForest, magrittr, plyr, methods, dplyr, keras, tfdatasets
License: GPL (>= 2)
BugReports: https://github.com/RebeccaSalles/TSPred/issues
URL: https://github.com/RebeccaSalles/TSPred/wiki
RoxygenNote: 7.1.1
LazyData: true
Encoding: UTF-8
NeedsCompilation: no
Packaged: 2020-12-24 13:48:06 UTC; Rebecca