1 |
Kechagias, S. and Pipiras, V. (2015). Definitions and representations of multivariate long?range dependent time series, Journal of Time Series Analysis, 36, 1-25.
DOI
|
2 |
Kingma, D. and Ba, J. (2014). Adam: A method for stochastic optimization, arXiv:1412.6980.
|
3 |
Kohzadi, N., Boyd, M. S., Kermanshahi, B., and Kaastra, I. (1996). A comparison of artificial neural network and time series models for forecasting commodity prices, Neurocomputing, 10, 169-181.
DOI
|
4 |
Lobato, I. N. (1997). Consistency of the averaged cross-periodogram in long memory series, Journal of Time Series Analysis, 18, 137-155.
DOI
|
5 |
Sela, R. J. and Hurvich, C. M. (2008). Computationally efficient methods for two multivariate fractionally integrated models, Journal of Time Series Analysis, 30, 631-651.
DOI
|
6 |
Smith, E. M., Smith, J., Legg, P., and Francis, S. (2017). Predicting the occurrence of world news events using recurrent neural networks and auto-regressive moving average models, Advances in Computational Intelligence Systems, 191-202.
|
7 |
Termenon, N., Jaillard, A., Delon-Martin, C., and Achard, S. (2016). Reliability of graph analysis of resting state fMRI using test-retest dataset from the Human Connectome Project, Neuroimage, 142, 172-187.
DOI
|
8 |
Whittle, P. (1963). On the fitting of multivariate autoregressions, and the approximate canonical factorization of a spectral density matrix, Biometrika, 50, 129-134.
DOI
|
9 |
Aladag, C. H., Egrioglu, E., and Kadilar, C. (2009). Forecasting nonlinear time series with a hybrid methodology, Applied Mathematics Letters, 22, 1467-1470.
DOI
|
10 |
Baek, C., Kechagias, S., and Pipiras, V. (2018). Asymptotics of bivariate local Whittle estimators with applications to fractal connectivity, Preprint.
|
11 |
Gers, F. A., Schmidhuber, J., and Cummins, F. (2000). Learning to forget: continual prediction with LSTM, Neural Computation, 12, 2451-2471.
DOI
|
12 |
Granger, C. W. J. and Joyeux, R. (1980). An introduction to long?memory time series models and fractional differencing, Journal of Time Series Analysis, 1, 15-39.
DOI
|
13 |
Hinton, G. E., Srivastava, N., Krizhevsky, A., Sutskever, I., and Salakhutdinov, R. R. (2012). Improving neural networks by preventing co-adaptation of feature detectors, arXiv:1207.0580.
|
14 |
Ho, S. L., Xie, M., and Goh, T. N. (2002). A comparative study of neural network and Box-Jenkins ARIMA modeling in time series prediction, Computers & Industrial Engineering, 42, 371-375.
DOI
|
15 |
Hyndman, R. J. (2006). Another look at forecast-accuracy metrics for intermittent demand, Foresight: The International Journal of Applied Forecasting, 4, 43-46.
|
16 |
Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory, Neural Computation, 9, 1735-1780.
DOI
|
17 |
Hosking, J. R. M. (1981). Fractional differencing, Biometrika, 68, 165-176.
DOI
|