Цитирование: | 1. Poskitt, D.S. and Tremayne, A.R., The Selection and Use of Linear and Bilinear Time Series Models, Int. J. Forecasting, 1986, vol. 2, no. 1, pp. 101–114.
2. Tong, H., Non-linear Time Series: A Dynamical System Approach, Oxford, UK: Clarendon, 1990.
3. Tong, H., Threshold Models in Non-linear Time Series Analysis, Lect. Notes Statist., vol. 21, Berlin: Springer, 1983.
4. Tong, H. and Lim, K.S., Threshold Autoregression, Limit Cycles and Cyclical Data, J. Roy. Statist. Soc. Ser. B, 1980, vol. 42, no. 3. 245–292.
5. Engle, R.F., Autoregressive Conditional Heteroscedasticity with Estimates of the Variance of United Kingdom Inflation, Econometrica, 1982, vol. 50, pp. 987–1007.
6. Bontempi, G., Local Learning Techniques for Modeling, Prediction and Control, PhD Thesis, IRIDIA, Université Libre de Bruxelles, Belgium, 1999.
7. Zhang, G., Patuwo, B.E., and Hu, M.Y., Forecasting with Artifcial Neural Networks: The State of the Art, Int. J. Forecasting, 1998, vol. 14, no. 1, pp. 35–62.
8. Cheng, H., Tan, P.-N., Gao, J., and Scripps, J., Multistep-Ahead Time Series Prediction, Advances in Knowledge Discovery and Data Mining (Proc. 10th Pacific-Asia Conf. PAKDD’2006, Singapore, Apr. 9–12, 2006), Ng, W.K., Kitsuregawa, M., Li, J., and Chang, K., Eds., Lect. Notes Comp. Sci., vol. 3918, Berlin: Springer, 2006, pp. 765–774.
9. Ryabko, B.Ya., Prediction of Random Sequences and Universal Coding, Probl. Peredachi Inf., 1988, vol. 24, no. 2, pp. 3–14 [Probl. Inf. Trans. (Engl. Transl.), 1988, vol. 24, no. 2, pp. 87–96].
10. Ryabko, B.Ya. and Monarev, V.A., Experimental Investigation of Forecasting Methods Based on Data Compression Algorithms, Probl. Peredachi Inf., 2005, vol. 41, no. 1, pp. 74–78 [Probl. Inf. Trans. (Engl. Transl.), 2005, vol. 41, no. 1, pp. 65–69].
11. Ryabko, B., Compression-Based Methods for Nonparametric Prediction and Estimation of Some Characteristics of Time Series, IEEE Trans. Inform. Theory, 2009, vol. 55, no. 9, pp. 4309–4315.
12. Cover, T.M. and Thomas, J.A., Elements of Information Theory, Hoboken, NJ: Wiley, 2006, 2nd ed.
13. Ryabko, B.Ya., Twice-Universal Coding, Probl. Peredachi Inf., 1984, vol. 20, no. 3, pp. 24–28 [Probl. Inf. Trans. (Engl. Transl.), 1984, vol. 20, no. 3, pp. 173–177].
14. Krichevskii, R.E., The Relation Between Redundancy Coding and Reliability of Information from a Source, Probl. Peredachi Inf., 1968, vol. 4, no. 3, pp. 48–57 [Probl. Inf. Trans. (Engl. Transl.), 1968, vol. 4, no. 3, pp. 37–45].
15. Krichevsky, R., Universal Compression and Retrieval, Dordrecht: Kluwer, 1993.
16. Ryabko, B.Y., Astola, J., and Gammerman, A., Adaptive Coding and Prediction of Sources with Large and Infinite Alphabets, IEEE Trans. Inform. Theory, 2008, vol. 54, no. 8, pp. 3808–3813.
17. Gasoline and Diesel Fuel Update, Independent Statistics & Analysis, U.S. Energy Information Administration, http://wwweiagov/petroleum/gasdiesel/.
|