Time Series Forecasting with Neural Networks

Automatic time series modelling with neural networks. Allows fully automatic, semi-manual or fully manual specification of networks. For details of the specification methodology see: (i) Crone and Kourentzes (2010) ; and (ii) Kourentzes et al. (2014) .

Time series modelling with neural networks for R: nnfor package

Development repository for the nnfor package for R. Stable version available on CRAN.

Installing

To install the development version use:

if (!require("devtools")){install.packages("devtools")}
devtools::install_github("trnnick/nnfor")

Otherwise, install the stable version from CRAN:

install.packages("nnfor")

Tutorial

You can find a tutorial on using nnfor for time series forecasting here.

Author

Nikolaos Kourentzes - (http://nikolaos.kourentzes.com/)

References

For an introduction to neural networks see for time series forecasting see: Ord K., Fildes R., Kourentzes N. (2017) Principles of Business Forecasting 2e. Wessex Press Publishing Co., Chapter 10.
For ensemble combination operators see: Kourentzes N., Barrow B.K., Crone S.F. (2014) Neural network ensemble operators for time series forecasting. Expert Systems with Applications, 41(9), 4235-4244.
For variable selection see: Crone S.F., Kourentzes N. (2010) Feature selection for time series prediction – A combined filter and wrapper approach for neural networks. Neurocomputing, 73(10), 1923-1936.