TSPred-package: Functions for Benchmarking Time Series Prediction
In TSPred: Functions for Benchmarking Time Series Prediction
Description
Functions for time series 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.
Author(s)
Rebecca Pontes Salles
Maintainer: rebeccapsalles@acm.org
TSPred documentation built on Jan. 21, 2021, 5:10 p.m.
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Description
Functions for time series 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.
Author(s)
Rebecca Pontes Salles
Maintainer: rebeccapsalles@acm.org
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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