11.6 拓展阅读

  • De Livera et al. (2011) 介绍了 TBATS 模型并一般性地讨论了复杂季节性的问题。
  • Pfaff (2008) 的书对 VAR 建模和其他多变量时间序列模型进行了概述。
  • 对单个时间序列,神经网络预测的预测结果往往不会很好。 Crone, Hibon, & Nikolopoulos (2011) 在预测竞赛的背景下讨论了这个问题。
  • Lahiri (2003) 讨论了时间序列的 bootstrap 。
  • 时间序列预测的 bagging 是相对较新的方法。 Bergmeir et al. (2016) 是讨论这个话题的为数不多的论文之一。

参考文献

Bergmeir, C., Hyndman, R. J., & Benítez, J. M. (2016). Bagging exponential smoothing methods using STL decomposition and Box-Cox transformation. International Journal of Forecasting, 32(2), 303–312. https://robjhyndman.com/publications/bagging-ets/

Crone, S. F., Hibon, M., & Nikolopoulos, K. (2011). Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction. International Journal of Forecasting, 27(3), 635–660. https://doi.org/10.1016/j.ijforecast.2011.04.001

De Livera, A. M., Hyndman, R. J., & Snyder, R. D. (2011). Forecasting time series with complex seasonal patterns using exponential smoothing. J American Statistical Association, 106(496), 1513–1527. https://robjhyndman.com/publications/complex-seasonality/

Lahiri, S. N. (2003). Resampling methods for dependent data. New York, USA: Springer Science & Business Media. [Amazon]

Pfaff, B. (2008). Analysis of integrated and cointegrated time series with R. New York, USA: Springer Science & Business Media. [Amazon]