11.6 Further reading
- De Livera, Hyndman, and Snyder (2011) introduced the TBATS model and discuss the problem of complex seasonality in general.
- Pfaff (2008) provides a book-length overview of VAR modelling and other multivariate time series models.
- Neural networks for individual time series have not tended to produce good forecasts. Crone, Hibon, and Nikolopoulos (2011) discuss this issue in the context of a forecasting competition.
- Bootstrapping for time series is discussed in Lahiri (2013).
- Bagging for time series forecasting is relatively new. Bergmeir, Hyndman, and Benitez (2016) is one of the few papers which addresses this topic.
De Livera, Alysha M, Rob J Hyndman, and Ralph D Snyder. 2011. “Forecasting Time Series with Complex Seasonal Patterns Using Exponential Smoothing.” Journal of the American Statistical Association 106 (496):1513–27.
Pfaff, Bernhard. 2008. Analysis of Integrated and Cointegrated Time Series with R. New York, USA: Springer Science & Business Media.
Crone, Sven F, Michele Hibon, and Konstantinos Nikolopoulos. 2011. “Advances in Forecasting with Neural Networks? Empirical Evidence from the Nn3 Competition on Time Series Prediction.” International Journal of Forecasting 27 (3). Elsevier:635–60.
Lahiri, Soumendra Nath. 2013. Resampling Methods for Dependent Data. New York, USA: Springer Science & Business Media.
Bergmeir, Christoph, Rob J Hyndman, and José M Benitez. 2016. “Bagging Exponential Smoothing Methods Using STL Decomposition and Box-Cox Transformation.” International Journal of Forecasting 32 (2):303–12.