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Generalising about univariate forecasting methods: further empirical evidence

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Cited by:

  1. Ralph D Snyder, 2005. "A Pedant's Approach to Exponential Smoothing," Monash Econometrics and Business Statistics Working Papers 5/05, Monash University, Department of Econometrics and Business Statistics.
  2. Qian, Lixian & Soopramanien, Didier, 2014. "Using diffusion models to forecast market size in emerging markets with applications to the Chinese car market," Journal of Business Research, Elsevier, vol. 67(6), pages 1226-1232.
  3. Madden, Gary & Tan, Joachim, 2007. "Forecasting telecommunications data with linear models," Telecommunications Policy, Elsevier, vol. 31(1), pages 31-44, February.
  4. Gardner, Everette Jr. & Diaz-Saiz, Joaquin, 2002. "Seasonal adjustment of inventory demand series: a case study," International Journal of Forecasting, Elsevier, vol. 18(1), pages 117-123.
  5. Tych, Wlodek & Pedregal, Diego J. & Young, Peter C. & Davies, John, 2002. "An unobserved component model for multi-rate forecasting of telephone call demand: the design of a forecasting support system," International Journal of Forecasting, Elsevier, vol. 18(4), pages 673-695.
  6. Svetunkov, Ivan & Chen, Huijing & Boylan, John E., 2023. "A new taxonomy for vector exponential smoothing and its application to seasonal time series," European Journal of Operational Research, Elsevier, vol. 304(3), pages 964-980.
  7. Hyndman, Rob J., 2020. "A brief history of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 36(1), pages 7-14.
  8. Ord, Keith & Hibon, Michele & Makridakis, Spyros, 2000. "The M3-Competition1," International Journal of Forecasting, Elsevier, vol. 16(4), pages 433-436.
  9. Armstrong, J. Scott & Green, Kesten C. & Graefe, Andreas, 2015. "Golden rule of forecasting: Be conservative," Journal of Business Research, Elsevier, vol. 68(8), pages 1717-1731.
  10. Robert Fildes & Gary Madden & Joachim Tan, 2007. "Optimal forecasting model selection and data characteristics," Applied Financial Economics, Taylor & Francis Journals, vol. 17(15), pages 1251-1264.
  11. Fildes, Robert & Kumar, V., 2002. "Telecommunications demand forecasting--a review," International Journal of Forecasting, Elsevier, vol. 18(4), pages 489-522.
  12. Assimakopoulos, V. & Nikolopoulos, K., 2000. "The theta model: a decomposition approach to forecasting," International Journal of Forecasting, Elsevier, vol. 16(4), pages 521-530.
  13. Madden, Gary G & Coble-Neal, Grant, 2005. "Forecasting international bandwidth capability," MPRA Paper 10822, University Library of Munich, Germany.
  14. R Fildes & K Nikolopoulos & S F Crone & A A Syntetos, 2008. "Forecasting and operational research: a review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(9), pages 1150-1172, September.
  15. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
  16. Sylvia Mardiana & Ferdinand Saragih & Martani Huseini, 2020. "Forecasting Gasoline Demand in Indonesia Using Time Series," International Journal of Energy Economics and Policy, Econjournals, vol. 10(6), pages 132-145.
  17. Armstrong, J. Scott, 2006. "Findings from evidence-based forecasting: Methods for reducing forecast error," International Journal of Forecasting, Elsevier, vol. 22(3), pages 583-598.
  18. De Gooijer, Jan G. & Hyndman, Rob J., 2006. "25 years of time series forecasting," International Journal of Forecasting, Elsevier, vol. 22(3), pages 443-473.
  19. López Menéndez, Ana Jesús & Pérez Suárez, Rigoberto, 2017. "Forecasting Performance and Information Measures. Revisiting the M-Competition /Evaluación de Predicciones y Medidas de Información. Reexamen de la M-Competición," Estudios de Economia Aplicada, Estudios de Economia Aplicada, vol. 35, pages 299-314, Mayo.
  20. Kourentzes, Nikolaos, 2014. "On intermittent demand model optimisation and selection," International Journal of Production Economics, Elsevier, vol. 156(C), pages 180-190.
  21. Bera, Soumitra Kumar, 2010. "Forecasting model of small scale industrial sector of West Bengal," MPRA Paper 28144, University Library of Munich, Germany.
  22. Fildes, Robert & Petropoulos, Fotios, 2015. "Is there a Golden Rule?," Journal of Business Research, Elsevier, vol. 68(8), pages 1742-1745.
  23. Li, Zheng & Rose, John M. & Hensher, David A., 2010. "Forecasting automobile petrol demand in Australia: An evaluation of empirical models," Transportation Research Part A: Policy and Practice, Elsevier, vol. 44(1), pages 16-38, January.
  24. Crone, Sven F. & Hibon, Michèle & Nikolopoulos, Konstantinos, 2011. "Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction," International Journal of Forecasting, Elsevier, vol. 27(3), pages 635-660.
  25. Fildes, Robert & Petropoulos, Fotios, 2015. "Simple versus complex selection rules for forecasting many time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1692-1701.
  26. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  27. Makridakis, Spyros & Hibon, Michele, 2000. "The M3-Competition: results, conclusions and implications," International Journal of Forecasting, Elsevier, vol. 16(4), pages 451-476.
  28. Gary Madden & Joachim Tan, 2008. "Forecasting international bandwidth capacity using linear and ANN methods," Applied Economics, Taylor & Francis Journals, vol. 40(14), pages 1775-1787.
  29. Svetunkov, Ivan & Kourentzes, Nikolaos, 2015. "Complex Exponential Smoothing," MPRA Paper 69394, University Library of Munich, Germany.
  30. D’Ignazio, Alessio & Giovannetti, Emanuele, 2015. "Predicting internet commercial connectivity wars: The impact of trust and operators’ asymmetry," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1127-1137.
  31. Jan G. de Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Tinbergen Institute Discussion Papers 05-068/4, Tinbergen Institute.
  32. Meade, Nigel, 2000. "A note on the Robust Trend and ARARMA methodologies used in the M3 Competition," International Journal of Forecasting, Elsevier, vol. 16(4), pages 517-519.
  33. Arora, Siddharth & Taylor, James W., 2016. "Forecasting electricity smart meter data using conditional kernel density estimation," Omega, Elsevier, vol. 59(PA), pages 47-59.
  34. Lars Lien Ankile & Kjartan Krange, 2022. "Deep Learning and Linear Programming for Automated Ensemble Forecasting and Interpretation," Papers 2201.00426, arXiv.org, revised Nov 2022.
  35. Evanschitzky, Heiner & Armstrong, J. Scott, 2010. "Replications of forecasting research," International Journal of Forecasting, Elsevier, vol. 26(1), pages 4-8, January.
  36. K. Maris & G. Pantou & K. Nikolopoulos & E. PagourtzI & V. Assimakopoulos, 2004. "A study of financial volatility forecasting techniques in the FTSE/ASE 20 index," Applied Economics Letters, Taylor & Francis Journals, vol. 11(7), pages 453-457.
  37. Chethana Dharmawardane & Ville Sillanpää & Jan Holmström, 2021. "High-frequency forecasting for grocery point-of-sales: intervention in practice and theoretical implications for operational design," Operations Management Research, Springer, vol. 14(1), pages 38-60, June.
  38. A H C Eaves & B G Kingsman, 2004. "Forecasting for the ordering and stock-holding of spare parts," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(4), pages 431-437, April.
  39. Ralph Snyder & Adrian Beaumont & J. Keith Ord, 2012. "Intermittent demand forecasting for inventory control: A multi-series approach," Monash Econometrics and Business Statistics Working Papers 15/12, Monash University, Department of Econometrics and Business Statistics.
  40. Madden, Gary & Savage, Scott J. & Coble-Neal, Grant, 2002. "Forecasting United States-Asia international message telephone service," International Journal of Forecasting, Elsevier, vol. 18(4), pages 523-543.
  41. Madden, Gary G & Coble-Neal, Grant, 2004. "Internet traffic dynamics," MPRA Paper 10827, University Library of Munich, Germany.
  42. Konstantinos Nikolopoulos, 2010. "Forecasting with quantitative methods: the impact of special events in time series," Applied Economics, Taylor & Francis Journals, vol. 42(8), pages 947-955.
  43. Taylor, James W., 2007. "Forecasting daily supermarket sales using exponentially weighted quantile regression," European Journal of Operational Research, Elsevier, vol. 178(1), pages 154-167, April.
  44. Anton A. Romanov & Aleksey A. Filippov & Valeria V. Voronina & Gleb Guskov & Nadezhda G. Yarushkina, 2021. "Modeling the Context of the Problem Domain of Time Series with Type-2 Fuzzy Sets," Mathematics, MDPI, vol. 9(22), pages 1-16, November.
  45. Garcia-Ferrer, A. & de Juan, A. & Poncela, P., 2006. "Forecasting traffic accidents using disaggregated data," International Journal of Forecasting, Elsevier, vol. 22(2), pages 203-222.
  46. R Fildes & B Kingsman, 2011. "Incorporating demand uncertainty and forecast error in supply chain planning models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 483-500, March.
  47. Gardner Jr., Everette S. & Diaz-Saiz, Joaquin, 2008. "Exponential smoothing in the telecommunications data," International Journal of Forecasting, Elsevier, vol. 24(1), pages 170-174.
  48. J W Taylor, 2011. "Multi-item sales forecasting with total and split exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(3), pages 555-563, March.
  49. Taylor, James W., 2008. "Exponentially weighted information criteria for selecting among forecasting models," International Journal of Forecasting, Elsevier, vol. 24(3), pages 513-524.
  50. O'Connor, Marcus & Remus, William & Griggs, Kenneth, 2000. "Does updating judgmental forecasts improve forecast accuracy?," International Journal of Forecasting, Elsevier, vol. 16(1), pages 101-109.
  51. Mun, Mak Kit & Chong, Choo Wei, 2018. "Forecasting Movie Demand Using Total and Split Exponential Smoothing," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(2), pages 81-94.
  52. Meade, Nigel & Islam, Towhidul, 2015. "Forecasting in telecommunications and ICT—A review," International Journal of Forecasting, Elsevier, vol. 31(4), pages 1105-1126.
  53. Sofia-ira KTENA & Fotios PETROPOULOS & Polychronis KOUTSOLIAKOS & Dimitrios MICHOS & Vassilios ASSIMAKOPOULOS, 2011. "Forecasting Sales in a Sugar Factory," Journal of Knowledge Management, Economics and Information Technology, ScientificPapers.org, vol. 1(7), pages 1-12, December.
  54. E. Andrew Boyd & Ioana C. Bilegan, 2003. "Revenue Management and E-Commerce," Management Science, INFORMS, vol. 49(10), pages 1363-1386, October.
  55. Pritularga, Kandrika F. & Svetunkov, Ivan & Kourentzes, Nikolaos, 2023. "Shrinkage estimator for exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1351-1365.
  56. Thomassey, Sebastien & Happiette, Michel & Castelain, Jean-Marie, 2005. "A global forecasting support system adapted to textile distribution," International Journal of Production Economics, Elsevier, vol. 96(1), pages 81-95, April.
  57. Tashman, Leonard J., 2000. "Out-of-sample tests of forecasting accuracy: an analysis and review," International Journal of Forecasting, Elsevier, vol. 16(4), pages 437-450.
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