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25 years of time series forecasting

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  • De Gooijer, Jan G.
  • Hyndman, Rob J.

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Article provided by Elsevier in its journal International Journal of Forecasting.

Volume (Year): 22 (2006)
Issue (Month): 3 ()
Pages: 443-473

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Handle: RePEc:eee:intfor:v:22:y:2006:i:3:p:443-473

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  1. Majid Delavari & Nadiya Gandali Alikhani & Esmaeil Naderi, 2013. "Do Dynamic Neural Networks Stand a Better Chance in Fractionally Integrated Process Forecasting?," International Journal of Economics and Financial Issues, Econjournals, vol. 3(2), pages 466-475.
  2. Guidi, Francesco, 2010. "Modelling and forecasting volatility of East Asian Newly Industrialized Countries and Japan stock markets with non-linear models," MPRA Paper 19851, University Library of Munich, Germany.
  3. Mishra, G. C. & Singh, A., 2013. "A Study on Forecasting Prices of Groundnut Oil in Delhi by Arima Methodology and Artificial Neural Networks," AGRIS on-line Papers in Economics and Informatics, Czech University of Life Sciences Prague, Faculty of Economics and Management, vol. 5(3), September.
  4. K. Triantafyllopoulos, 2008. "Multivariate stochastic volatility with Bayesian dynamic linear models," Papers 0802.0214, arXiv.org.
  5. Kim, Jae H. & Wong, Kevin & Athanasopoulos, George & Liu, Shen, 2011. "Beyond point forecasting: Evaluation of alternative prediction intervals for tourist arrivals," International Journal of Forecasting, Elsevier, vol. 27(3), pages 887-901.
  6. Michael Wolf & Dan Wunderli, 2012. "Bootstrap joint prediction regions," ECON - Working Papers 064, Department of Economics - University of Zurich, revised May 2013.
  7. Croux, C. & Gelper, S. & Mahieu, K., 2010. "Robust Control Charts for Time Series Data," Discussion Paper 2010-107, Tilburg University, Center for Economic Research.
  8. Peroni, Chiara, 2007. "A non-parametric investigation of risk premia," MPRA Paper 5126, University Library of Munich, Germany, revised 01 Dec 2007.
  9. Teddy, S.D. & Ng, S.K., 2011. "Forecasting ATM cash demands using a local learning model of cerebellar associative memory network," International Journal of Forecasting, Elsevier, vol. 27(3), pages 760-776, July.
  10. Jeffrey S. Racine & Christopher F. Parmeter, 2012. "Data-Driven Model Evaluation: A Test for Revealed Performance," Department of Economics Working Papers 2012-13, McMaster University.
  11. Chew Lian Chua & G. C. Lim & Sarantis Tsiaplias, 2012. "A latent variable approach to forecasting the unemployment rate," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 31(3), pages 229-244, 04.
  12. Syntetos, Aris A. & Nikolopoulos, Konstantinos & Boylan, John E. & Fildes, Robert & Goodwin, Paul, 2009. "The effects of integrating management judgement into intermittent demand forecasts," International Journal of Production Economics, Elsevier, vol. 118(1), pages 72-81, March.
  13. Wong, W.K. & Guo, Z.X., 2010. "A hybrid intelligent model for medium-term sales forecasting in fashion retail supply chains using extreme learning machine and harmony search algorithm," International Journal of Production Economics, Elsevier, vol. 128(2), pages 614-624, December.
  14. Masayoshi Hayashi, 2012. "Forecasting Welfare Caseloads: The Case of the Japanese Public Assistance Program," CIRJE F-Series CIRJE-F-846, CIRJE, Faculty of Economics, University of Tokyo.
  15. Savio, Nicolas D. & Nikolopoulos, Konstantinos, 2013. "A strategic forecasting framework for governmental decision-making and planning," International Journal of Forecasting, Elsevier, vol. 29(2), pages 311-321.
  16. Claudio Felisoni de Angelo & Ronaldo Zwicker & Nuno Manoel Martins Dias Fouto & Marcos Roberto Luppe, 2011. "Temporal series and neural networks: a comparative analysis of techniques in the Brazilian retail sales forecast," Brazilian Business Review, Fucape Business School, vol. 8(2), pages 01-21, April.
  17. Ling He & Chenyi Hu, 2009. "Impacts of Interval Computing on Stock Market Variability Forecasting," Computational Economics, Society for Computational Economics, vol. 33(3), pages 263-276, April.
  18. repec:eme:jrfpps:v:10:y:2010:i:4:p:410-415 is not listed on IDEAS
  19. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.

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