nnfor (version 0.9.2)

nnfor-package: nnfor: Time Series Forecasting with Neural Networks

Description

Contains functions to facilitate 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) <doi:10.1016/j.neucom.2010.01.017>; and (ii) Kourentzes et al. (2014) <doi:10.1016/j.eswa.2013.12.011>.

References

• For an introduction to neural networks 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 <U+2013> A combined filter and wrapper approach for neural networks. Neurocomputing, 73(10), 1923-1936.

See Also

Useful links:

• http://kourentzes.com/forecasting/2017/02/10/forecasting-time-series-with-neural-networks-in-r/

• Report bugs at https://github.com/trnnick/nnfor/issues