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Forecasting Sales by Exponentially Weighted Moving Averages

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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. Pleños, Mary Cris F., 2022. "Time Series Forecasting Using Holt-Winters Exponential Smoothing: Application to Abaca Fiber Data," Problems of World Agriculture / Problemy Rolnictwa Światowego, Warsaw University of Life Sciences, vol. 22(2), June.
  3. Rice, William L. & Park, So Young & Pan, Bing & Newman, Peter, 2019. "Forecasting campground demand in US national parks," Annals of Tourism Research, Elsevier, vol. 75(C), pages 424-438.
  4. Mr. Atsushi Iimi, 2006. "Exchange Rate Misalignment: An Application of the Behavioral Equilibrium Exchange Rate (BEER) to Botswana," IMF Working Papers 2006/140, International Monetary Fund.
  5. Kosuke Kawakami & Hirokazu Kobayashi & Kazuhide Nakata, 2021. "Seasonal Inventory Management Model for Raw Materials in Steel Industry," Interfaces, INFORMS, vol. 51(4), pages 312-324, July.
  6. Stefan Mihai Petrea & Cristina Zamfir & Ira Adeline Simionov & Alina Mogodan & Florian Marcel Nuţă & Adrian Turek Rahoveanu & Dumitru Nancu & Dragos Sebastian Cristea & Florin Marian Buhociu, 2021. "A Forecasting and Prediction Methodology for Improving the Blue Economy Resilience to Climate Change in the Romanian Lower Danube Euroregion," Sustainability, MDPI, vol. 13(21), pages 1-36, October.
  7. Trull, Oscar & García-Díaz, J. Carlos & Troncoso, Alicia, 2021. "One-day-ahead electricity demand forecasting in holidays using discrete-interval moving seasonalities," Energy, Elsevier, vol. 231(C).
  8. Daniel C Medina & Sally E Findley & Boubacar Guindo & Seydou Doumbia, 2007. "Forecasting Non-Stationary Diarrhea, Acute Respiratory Infection, and Malaria Time-Series in Niono, Mali," PLOS ONE, Public Library of Science, vol. 2(11), pages 1-13, November.
  9. Tsao, Yu-Chung & Chen, Yu-Kai & Chiu, Shih-Hao & Lu, Jye-Chyi & Vu, Thuy-Linh, 2022. "An innovative demand forecasting approach for the server industry," Technovation, Elsevier, vol. 110(C).
  10. A A Syntetos & J E Boylan & S M Disney, 2009. "Forecasting for inventory planning: a 50-year review," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(1), pages 149-160, May.
  11. P. A. Nazarov & Kazakova, Maria, 2014. "Theoretical Basis of Prediction of Main Budget Parameters of Country," Published Papers r90221, Russian Presidential Academy of National Economy and Public Administration.
  12. Oleksandr Melnychenko & Valerii Matskul & Tetiana Osadcha, 2022. "The Dynamics of Trade Relations between Ukraine and Romania: Modelling and Forecasting," Virtual Economics, The London Academy of Science and Business, vol. 5(2), pages 7-23, July.
  13. Andrea Kolková & Aleksandr Kljuènikov, 2021. "Demand forecasting: an alternative approach based on technical indicator Pbands," Oeconomia Copernicana, Institute of Economic Research, vol. 12(4), pages 1063-1094, December.
  14. 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.
  15. George Athanasopoulos & Ashton de Silva, 2010. "Multivariate exponential smoothing for forecasting tourist arrivals to Australia and New Zealand," Monash Econometrics and Business Statistics Working Papers 11/09, Monash University, Department of Econometrics and Business Statistics.
  16. 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.
  17. Sebastien Valeyre, 2022. "Optimal trend following portfolios," Papers 2201.06635, arXiv.org.
  18. Vesna Karadzic & Bojan Pejovic, 2021. "Inflation Forecasting in the Western Balkans and EU: A Comparison of Holt-Winters, ARIMA and NNAR Models," The AMFITEATRU ECONOMIC journal, Academy of Economic Studies - Bucharest, Romania, vol. 23(57), pages 517-517.
  19. Billah, Baki & King, Maxwell L. & Snyder, Ralph D. & Koehler, Anne B., 2006. "Exponential smoothing model selection for forecasting," International Journal of Forecasting, Elsevier, vol. 22(2), pages 239-247.
  20. Segura, J. V. & Vercher, E., 2001. "A spreadsheet modeling approach to the Holt-Winters optimal forecasting," European Journal of Operational Research, Elsevier, vol. 131(2), pages 375-388, June.
  21. Li, Qinyun & Gaalman, Gerard & Disney, Stephen M., 2023. "On the equivalence of the proportional and damped trend order-up-to policies: An eigenvalue analysis," International Journal of Production Economics, Elsevier, vol. 265(C).
  22. Haensel, Alwin & Koole, Ger, 2011. "Booking horizon forecasting with dynamic updating: A case study of hotel reservation data," International Journal of Forecasting, Elsevier, vol. 27(3), pages 942-960, July.
  23. Hyunjin Lee & Taesik Lee, 2021. "Demand modelling for emergency medical service system with multiple casualties cases: k-inflated mixture regression model," Flexible Services and Manufacturing Journal, Springer, vol. 33(4), pages 1090-1115, December.
  24. Denafas, Gintaras & Ruzgas, Tomas & Martuzevičius, Dainius & Shmarin, Sergey & Hoffmann, Michael & Mykhaylenko, Valeriy & Ogorodnik, Stanislav & Romanov, Mikhail & Neguliaeva, Ekaterina & Chusov, Alex, 2014. "Seasonal variation of municipal solid waste generation and composition in four East European cities," Resources, Conservation & Recycling, Elsevier, vol. 89(C), pages 22-30.
  25. Sarah Gelper & Roland Fried & Christophe Croux, 2010. "Robust forecasting with exponential and Holt-Winters smoothing," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 29(3), pages 285-300.
  26. Dinis, Duarte & Barbosa-Póvoa, Ana & Teixeira, Ângelo Palos, 2022. "Enhancing capacity planning through forecasting: An integrated tool for maintenance of complex product systems," International Journal of Forecasting, Elsevier, vol. 38(1), pages 178-192.
  27. Jiyoung Park & James E. Moore & Peter Gordon & Harry W. Richardson, 2017. "A New Approach to Quantifying the Impact of Hurricane-Disrupted Oil Refinery Operations Utilizing Secondary Data," Group Decision and Negotiation, Springer, vol. 26(6), pages 1125-1144, November.
  28. Costache, Mioara & Sebastian Cristea, Dragos & Petrea, Stefan-Mihai & Neculita, Mihaela & Rahoveanu, Maria Magdalena Turek & Simionov, Ira-Adeline & Mogodan, Alina & Sarpe, Daniela & Rahoveanu, Adrian, 2021. "Integrating aquaponics production systems into the Romanian green procurement network," Land Use Policy, Elsevier, vol. 108(C).
  29. Gaetano Perone, 2022. "Comparison of ARIMA, ETS, NNAR, TBATS and hybrid models to forecast the second wave of COVID-19 hospitalizations in Italy," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 23(6), pages 917-940, August.
  30. Seong, Byeongchan & Lee, Kiseop, 2021. "Intervention analysis based on exponential smoothing methods: Applications to 9/11 and COVID-19 effects," Economic Modelling, Elsevier, vol. 98(C), pages 290-301.
  31. Hess, Alexander & Spinler, Stefan & Winkenbach, Matthias, 2021. "Real-time demand forecasting for an urban delivery platform," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
  32. Mohit Apte & Yashodhara Haribhakta, 2024. "Advancing Financial Forecasting: A Comparative Analysis of Neural Forecasting Models N-HiTS and N-BEATS," Papers 2409.00480, arXiv.org, revised Sep 2024.
  33. Xiaodan Zhu & Anh Ninh & Hui Zhao & Zhenming Liu, 2021. "Demand Forecasting with Supply‐Chain Information and Machine Learning: Evidence in the Pharmaceutical Industry," Production and Operations Management, Production and Operations Management Society, vol. 30(9), pages 3231-3252, September.
  34. Yuliya S. Evlakhova & Alexandra A. Tregubova, 2023. "Russian Market of Online Microloans to the Population: Credit Risks Analysis," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 22(3), pages 710-738.
  35. Rajapaksha, Dilini & Bergmeir, Christoph & Hyndman, Rob J., 2023. "LoMEF: A framework to produce local explanations for global model time series forecasts," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1424-1447.
  36. Andrea Kolková & Petr Rozehnal, 2022. "Hybrid demand forecasting models: pre-pandemic and pandemic use studies," Equilibrium. Quarterly Journal of Economics and Economic Policy, Institute of Economic Research, vol. 17(3), pages 699-725, September.
  37. Jiang, Weiheng & Wu, Xiaogang & Gong, Yi & Yu, Wanxin & Zhong, Xinhui, 2020. "Holt–Winters smoothing enhanced by fruit fly optimization algorithm to forecast monthly electricity consumption," Energy, Elsevier, vol. 193(C).
  38. Villegas, Marco A. & Pedregal, Diego J., 2019. "Automatic selection of unobserved components models for supply chain forecasting," International Journal of Forecasting, Elsevier, vol. 35(1), pages 157-169.
  39. Rodney L. Jacobs, 1978. "An Examination of the Economic and Muthian Rationality of Price Level Forecasts," UCLA Economics Working Papers 135A, UCLA Department of Economics.
  40. Jennifer Castle & David Hendry, 2012. "Forecasting by factors, by variables, or both?," Economics Series Working Papers 600, University of Oxford, Department of Economics.
  41. Benedict J. Drasch & Gilbert Fridgen & Lukas Häfner, 2020. "Demand response through automated air conditioning in commercial buildings—a data-driven approach," Business Research, Springer;German Academic Association for Business Research, vol. 13(3), pages 1491-1525, November.
  42. Naragain Phumchusri & Thiti Chewcharat & Supawish Kanokpongsakorn, 2024. "Price promotion optimization model for multiperiod planning: a case study of beauty category products sold in a convenience store chain," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 23(2), pages 164-178, April.
  43. Steenkamp, P. J. D. & Sartorius von Back, H. J. & Viviers, L. & Millard, S., 1995. "Marketing Margin Analysis Of South African Potatoes," Agrekon, Agricultural Economics Association of South Africa (AEASA), vol. 34(3), September.
  44. Niels Haldrup & Oskar Knapik & Tommaso Proietti, 2016. "A generalized exponential time series regression model for electricity prices," CREATES Research Papers 2016-08, Department of Economics and Business Economics, Aarhus University.
  45. Koehler, Anne B. & Snyder, Ralph D. & Ord, J. Keith, 2001. "Forecasting models and prediction intervals for the multiplicative Holt-Winters method," International Journal of Forecasting, Elsevier, vol. 17(2), pages 269-286.
  46. Ramos, Francisco López & Batres, Rafael & De-la-Cruz-Márquez, Cynthia Griselle & Anzures, Melina López, 2023. "Optimization models for nopal crop planning with land usage expansion and government subsidy," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
  47. Snyder, Ralph D. & Koehler, Anne B. & Hyndman, Rob J. & Ord, J. Keith, 2004. "Exponential smoothing models: Means and variances for lead-time demand," European Journal of Operational Research, Elsevier, vol. 158(2), pages 444-455, October.
  48. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  49. M A Rahman & B R Sarker & L A Escobar, 2011. "Peak demand forecasting for a seasonal product using Bayesian approach," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1019-1028, June.
  50. Feng Xu & Mohamad Sepehri & Jian Hua & Sergey Ivanov & Julius N. Anyu, 2018. "Time-Series Forecasting Models for Gasoline Prices in China," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 10(12), pages 1-43, December.
  51. Wang, Zheng-Xin & Wang, Zhi-Wei & Li, Qin, 2020. "Forecasting the industrial solar energy consumption using a novel seasonal GM(1,1) model with dynamic seasonal adjustment factors," Energy, Elsevier, vol. 200(C).
  52. George E. P. Box & Steven C. Hillmer & George C. Tiao, 1978. "Analysis and Modeling of Seasonal Time Series," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 309-344, National Bureau of Economic Research, Inc.
  53. Isabella Damdinovna Elyakova & Aleksandr Andreyevich Khristoforov & Aleksandr Lvovich Elyakov & Larisa Ivanovna Danilova & Tamara Aleksandrovna Karataeva & Elena Vladimirovna Danilova, 2017. "Forecast Scenarios of World Prices for Natural Gas," European Research Studies Journal, European Research Studies Journal, vol. 0(4A), pages 284-297.
  54. Hussain, Anwar & Rahman, Muhammad & Memon, Junaid Alam, 2016. "Forecasting electricity consumption in Pakistan: the way forward," Energy Policy, Elsevier, vol. 90(C), pages 73-80.
  55. Holt, Charles C., 2004. "Author's retrospective on 'Forecasting seasonals and trends by exponentially weighted moving averages'," International Journal of Forecasting, Elsevier, vol. 20(1), pages 11-13.
  56. Isra Al-Turaiki & Fahad Almutlaq & Hend Alrasheed & Norah Alballa, 2021. "Empirical Evaluation of Alternative Time-Series Models for COVID-19 Forecasting in Saudi Arabia," IJERPH, MDPI, vol. 18(16), pages 1-19, August.
  57. Yelena Vardanyan & Henrik Madsen, 2019. "Stochastic Bilevel Program for Optimal Coordinated Energy Trading of an EV Aggregator," Energies, MDPI, vol. 12(20), pages 1-18, October.
  58. Joan Mileski & Christopher Clott & Cassia Bomer Galvao & Taliese Laverne, 2020. "Technical analysis: the psychology of the market of dry bulk freight rates," Journal of Shipping and Trade, Springer, vol. 5(1), pages 1-15, December.
  59. Jozef Vilček & Štefan Koco & Eva Litavcová & Stanislav Torma, 2020. "Characteristics of Soil Parameters of Agricultural Land Use Types, Their Location and Development Forecast," Land, MDPI, vol. 9(6), pages 1-17, June.
  60. de Oliveira, Erick Meira & Cyrino Oliveira, Fernando Luiz, 2018. "Forecasting mid-long term electric energy consumption through bagging ARIMA and exponential smoothing methods," Energy, Elsevier, vol. 144(C), pages 776-788.
  61. Merten, Michael & Rücker, Fabian & Schoeneberger, Ilka & Sauer, Dirk Uwe, 2020. "Automatic frequency restoration reserve market prediction: Methodology and comparison of various approaches," Applied Energy, Elsevier, vol. 268(C).
  62. Inés Gómez-Acebo & Javier Llorca & Paz Rodríguez-Cundín & Trinidad Dierssen-Sotos, 2012. "Extreme temperatures and mortality in the North of Spain," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(2), pages 305-313, April.
  63. Klymenko, Nataliia & Voronenko, Iryna & Nehrey, Maryna & Rogoza, Konstyantyn & Rogoza, Nataliy, 2023. "Risk assessment of shock periods and investment attractiveness of agroholdings of Ukraine," Agricultural and Resource Economics: International Scientific E-Journal, Agricultural and Resource Economics: International Scientific E-Journal, vol. 9(2), June.
  64. Baloglu, Ulas Baran & Demir, Yakup, 2018. "Lightweight privacy-preserving data aggregation scheme for smart grid metering infrastructure protection," International Journal of Critical Infrastructure Protection, Elsevier, vol. 22(C), pages 16-24.
  65. Deb, Chirag & Zhang, Fan & Yang, Junjing & Lee, Siew Eang & Shah, Kwok Wei, 2017. "A review on time series forecasting techniques for building energy consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 902-924.
  66. Zhen Zeng & Tucker Balch & Manuela Veloso, 2021. "Deep Video Prediction for Time Series Forecasting," Papers 2102.12061, arXiv.org, revised Nov 2021.
  67. Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
  68. Beaumont, Adrian N., 2014. "Data transforms with exponential smoothing methods of forecasting," International Journal of Forecasting, Elsevier, vol. 30(4), pages 918-927.
  69. Snyder, Ralph D. & Koehler, Anne B. & Ord, J. Keith, 2002. "Forecasting for inventory control with exponential smoothing," International Journal of Forecasting, Elsevier, vol. 18(1), pages 5-18.
  70. Li, Qinyun & Disney, Stephen M. & Gaalman, Gerard, 2014. "Avoiding the bullwhip effect using Damped Trend forecasting and the Order-Up-To replenishment policy," International Journal of Production Economics, Elsevier, vol. 149(C), pages 3-16.
  71. Ferbar Tratar, Liljana & Mojškerc, Blaž & Toman, Aleš, 2016. "Demand forecasting with four-parameter exponential smoothing," International Journal of Production Economics, Elsevier, vol. 181(PA), pages 162-173.
  72. J. D. Bermudez & J. V. Segura & E. Vercher, 2007. "Holt-Winters Forecasting: An Alternative Formulation Applied to UK Air Passenger Data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 34(9), pages 1075-1090.
  73. Proietti, Tommaso, 2003. "Forecasting the US unemployment rate," Computational Statistics & Data Analysis, Elsevier, vol. 42(3), pages 451-476, March.
  74. Marvin Carl May & Alexander Albers & Marc David Fischer & Florian Mayerhofer & Louis Schäfer & Gisela Lanza, 2021. "Queue Length Forecasting in Complex Manufacturing Job Shops," Forecasting, MDPI, vol. 3(2), pages 1-17, May.
  75. 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.
  76. Meira, Erick & Cyrino Oliveira, Fernando Luiz & Jeon, Jooyoung, 2021. "Treating and Pruning: New approaches to forecasting model selection and combination using prediction intervals," International Journal of Forecasting, Elsevier, vol. 37(2), pages 547-568.
  77. Paris A. Mastorocostas & Constantinos S. Hilas & Dimitris N. Varsamis & Stergiani C. Dova, 2016. "Telecommunications call volume forecasting with a block-diagonal recurrent fuzzy neural network," Telecommunication Systems: Modelling, Analysis, Design and Management, Springer, vol. 63(1), pages 15-25, September.
  78. Pantazopoulos, Sotiris N. & Pappis, Costas P., 1996. "A new adaptive method for extrapolative forecasting algorithms," European Journal of Operational Research, Elsevier, vol. 94(1), pages 106-111, October.
  79. Javier Oliver Muncharaz, 2020. "Comparing classic time series models and the LSTM recurrent neural network: An application to S&P 500 stocks [Comparativa de los models clásicos de series temporales con la red neuronal recurrente ," Post-Print hal-03149342, HAL.
  80. Francis X. Diebold & Lutz Kilian & Marc Nerlove, 2006. "Time Series Analysis," PIER Working Paper Archive 06-019, Penn Institute for Economic Research, Department of Economics, University of Pennsylvania.
    • Diebold, F.X. & Kilian, L. & Nerlove, Marc, 2006. "Time Series Analysis," Working Papers 28556, University of Maryland, Department of Agricultural and Resource Economics.
  81. Harris, Richard D.F. & Yilmaz, Fatih, 2008. "Retrieving seasonally adjusted quarterly growth rates from annual growth rates that are reported quarterly," European Journal of Operational Research, Elsevier, vol. 188(3), pages 846-853, August.
  82. Donald A. Sylvan, 1976. "Consequences of Sharp Military Assistance Increases for International Conflict and Cooperation," Journal of Conflict Resolution, Peace Science Society (International), vol. 20(4), pages 609-636, December.
  83. Webel, Karsten, 2022. "A review of some recent developments in the modelling and seasonal adjustment of infra-monthly time series," Discussion Papers 31/2022, Deutsche Bundesbank.
  84. Liu, Yamei, 2000. "Overfitting and forecasting: linear versus non-linear time series models," ISU General Staff Papers 2000010108000014914, Iowa State University, Department of Economics.
  85. Theresa Maria Rausch & Tobias Albrecht & Daniel Baier, 2022. "Beyond the beaten paths of forecasting call center arrivals: on the use of dynamic harmonic regression with predictor variables," Journal of Business Economics, Springer, vol. 92(4), pages 675-706, May.
  86. Filelis - Papadopoulos, Christos K. & Kyziropoulos, Panagiotis E. & Morrison, John P. & O‘Reilly, Philip, 2022. "Modelling and forecasting based on recursive incomplete pseudoinverse matrices," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 197(C), pages 358-376.
  87. J. S. Armstrong & R. Brodie & S. McIntyre, 2005. "Forecasting Methods for Marketing:* Review of Empirical Research," General Economics and Teaching 0502023, University Library of Munich, Germany.
  88. Luis Uzeda, 2022. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," Advances in Econometrics, in: Essays in Honour of Fabio Canova, volume 44, pages 25-53, Emerald Group Publishing Limited.
  89. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
  90. Rossi, Barbara, 2013. "Advances in Forecasting under Instability," Handbook of Economic Forecasting, in: G. Elliott & C. Granger & A. Timmermann (ed.), Handbook of Economic Forecasting, edition 1, volume 2, chapter 0, pages 1203-1324, Elsevier.
  91. Hartzel, Kathleen S. & Wood, Charles A., 2017. "Factors that affect the improvement of demand forecast accuracy through point-of-sale reporting," European Journal of Operational Research, Elsevier, vol. 260(1), pages 171-182.
  92. Lawton, Richard, 1998. "How should additive Holt-Winters estimates be corrected?," International Journal of Forecasting, Elsevier, vol. 14(3), pages 393-403, September.
  93. Karamaziotis, Panagiotis I. & Raptis, Achilleas & Nikolopoulos, Konstantinos & Litsiou, Konstantia & Assimakopoulos, Vassilis, 2020. "An empirical investigation of water consumption forecasting methods," International Journal of Forecasting, Elsevier, vol. 36(2), pages 588-606.
  94. David F. Hendry & Michael P. Clements, 1994. "Can Econometrics Improve Economic Forecasting?," Swiss Journal of Economics and Statistics (SJES), Swiss Society of Economics and Statistics (SSES), vol. 130(III), pages 267-298, September.
  95. Naragain Phumchusri & Phoom Ungtrakul, 2020. "Hotel daily demand forecasting for high-frequency and complex seasonality data: a case study in Thailand," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 19(1), pages 8-25, February.
  96. Shehu Usman Rano, Aliyu, 2007. "Real Exchange Rate Misalignment: An Application of Behavioral Equilibrium Exchange Rate (BEER) to Nigeria," MPRA Paper 10376, University Library of Munich, Germany.
  97. Ahmad Farid Osman & Maxwell L. King, 2015. "A new approach to forecasting based on exponential smoothing with independent regressors," Monash Econometrics and Business Statistics Working Papers 2/15, Monash University, Department of Econometrics and Business Statistics.
  98. Chen, Jiandong & Xu, Chong & Shahbaz, Muhammad & Song, Malin, 2021. "Interaction determinants and projections of China’s energy consumption: 1997–2030," Applied Energy, Elsevier, vol. 283(C).
  99. Ghosh, Koushik & Basu, Tapasendra, 2015. "Search for the periodicity of the prime Indian and American stock exchange indices using date-compensated discrete Fourier transformAuthor-Name: Samadder, Swetadri," Chaos, Solitons & Fractals, Elsevier, vol. 77(C), pages 149-157.
  100. Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
  101. Meira, Erick & Lila, Maurício Franca & Cyrino Oliveira, Fernando Luiz, 2023. "A novel reconciliation approach for hierarchical electricity consumption forecasting based on resistant regression," Energy, Elsevier, vol. 269(C).
  102. Panja, Madhurima & Chakraborty, Tanujit & Nadim, Sk Shahid & Ghosh, Indrajit & Kumar, Uttam & Liu, Nan, 2023. "An ensemble neural network approach to forecast Dengue outbreak based on climatic condition," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
  103. Alexander Lvovich Elyakov & Isabella Damdinovna Elyakova & Larisa Ivanovna Danilova & Alexander Andreevich Khristoforov & Oleg Ilich Kondratev & Valentina Vasilyevna Grigoryeva, 2017. "History and Prospects of Natural Gas Pricing in Continental Europe in Conditions of Instability of World Oil Prices," European Research Studies Journal, European Research Studies Journal, vol. 0(4A), pages 323-338.
  104. Bianchi, Lisa & Jarrett, Jeffrey & Choudary Hanumara, R., 1998. "Improving forecasting for telemarketing centers by ARIMA modeling with intervention," International Journal of Forecasting, Elsevier, vol. 14(4), pages 497-504, December.
  105. Zhang, Kai & Yin, Kedong & Yang, Wendong, 2022. "Predicting bioenergy power generation structure using a newly developed grey compositional data model: A case study in China," Renewable Energy, Elsevier, vol. 198(C), pages 695-711.
  106. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
  107. Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.
  108. Daniela Pencheva, 2020. "Use of Factors Related to the Consumption of Fast Moving Consumer Goods in Business Intelligence System for Managing Orders to Suppliers in Retail Chain," Izvestia Journal of the Union of Scientists - Varna. Economic Sciences Series, Union of Scientists - Varna, Economic Sciences Section, vol. 9(2), pages 124-135, August.
  109. Trapero, Juan R. & Kourentzes, Nikolaos & Martin, A., 2015. "Short-term solar irradiation forecasting based on Dynamic Harmonic Regression," Energy, Elsevier, vol. 84(C), pages 289-295.
  110. Rossetti Renato, 2019. "Forecasting the Sales of Console Games for the Italian Market," Econometrics. Advances in Applied Data Analysis, Sciendo, vol. 23(3), pages 76-88, September.
  111. Honcharenko Tetiana P., 2014. "Assessing Seasonality in the Marketing System of Industrial Enterprises," Business Inform, RESEARCH CENTRE FOR INDUSTRIAL DEVELOPMENT PROBLEMS of NAS (KHARKIV, UKRAINE), Kharkiv National University of Economics, issue 2, pages 366-370.
  112. Peter M. Bernegger & Scott Webster, 2014. "Fixed-Cycle Smoothed Production Improves Lean Performance for Make-to-Stock Manufacturing," Interfaces, INFORMS, vol. 44(4), pages 411-427, August.
  113. 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.
  114. Sun, Zhentian & Li, Xuhong & Xie, Yuanchang, 2014. "A comparison of innovative financing and general fiscal investment strategies for second-class highways: Perspectives for building a sustainable financing strategy," Transport Policy, Elsevier, vol. 35(C), pages 193-201.
  115. Tasdemir, Cagatay & Hiziroglu, Salim, 2019. "Achieving cost efficiency through increased inventory leanness: Evidences from oriented strand board (OSB) industry," International Journal of Production Economics, Elsevier, vol. 208(C), pages 412-433.
  116. Egon Smeral & Michael Wüger, 2004. "Does Complexity Matter? Methods for Improving Forecasting Accuracy in Tourism," WIFO Working Papers 225, WIFO.
  117. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
  118. Hanlin Gao & Meiqing Zhang & Anne Goodchild, 2020. "Empirical Analysis of Relieving High-Speed Rail Freight Congestion in China," Sustainability, MDPI, vol. 12(23), pages 1-16, November.
  119. Azumah Karim & Ananda Omotukoh Kube & Bashiru Imoro Ibn Saeed, 2020. "Modeling of Monthly Meteorological Time Series," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 9(4), pages 1-8.
  120. Zhenni Ding & Huayou Chen & Ligang Zhou, 2023. "Using shapely values to define subgroups of forecasts for combining," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 905-923, July.
  121. Liang, Weifang & Liu, Yong & Somogyi, Simon & Anderson, David P., 2024. "A Multi-Model, Ensemble Approach to Forecasting United States Food Prices," 2024 Annual Meeting, July 28-30, New Orleans, LA 343687, Agricultural and Applied Economics Association.
  122. Smirnov, Dmitry & Huchzermeier, Arnd, 2020. "Analytics for labor planning in systems with load-dependent service times," European Journal of Operational Research, Elsevier, vol. 287(2), pages 668-681.
  123. Fieger, Peter & Rice, John, 2016. "Modelling Chinese Inbound Tourism Arrivals into Christchurch," MPRA Paper 75468, University Library of Munich, Germany.
  124. George Athanasopoulos & Rob J. Hyndman, 2006. "Modelling and forecasting Australian domestic tourism," Monash Econometrics and Business Statistics Working Papers 19/06, Monash University, Department of Econometrics and Business Statistics.
  125. Mihaela Cazacu & Emilia Ţiţan & Daniela-Ioana Manea & Mihaela Mihai, 2021. "The Impact of Digitalization in Mitigating the Effects of the COVID-19 Pandemic for Silver Population," Romanian Journal of Economics, Institute of National Economy, vol. 52(1(61)), pages 50-57, June.
  126. Petropoulos, Fotios & Makridakis, Spyros & Assimakopoulos, Vassilios & Nikolopoulos, Konstantinos, 2014. "‘Horses for Courses’ in demand forecasting," European Journal of Operational Research, Elsevier, vol. 237(1), pages 152-163.
  127. Sbrana, Giacomo & Pelagatti, Matteo, 2024. "Optimal hierarchical EWMA forecasting," International Journal of Forecasting, Elsevier, vol. 40(2), pages 616-625.
  128. So, Mike K.P. & Chung, Ray S.W., 2014. "Dynamic seasonality in time series," Computational Statistics & Data Analysis, Elsevier, vol. 70(C), pages 212-226.
  129. Veiga, Claudimar Pereira da & Veiga, Cássia Rita Pereira da & Puchalski, Weslly & Coelho, Leandro dos Santos & Tortato, Ubiratã, 2016. "Demand forecasting based on natural computing approaches applied to the foodstuff retail segment," Journal of Retailing and Consumer Services, Elsevier, vol. 31(C), pages 174-181.
  130. Hill, Arthur V. & Zhang, Weiyong & Burch, Gerald F., 2015. "Forecasting the forecastability quotient for inventory management," International Journal of Forecasting, Elsevier, vol. 31(3), pages 651-663.
  131. Aubry, Mathilde & Renou-Maissant, Patricia, 2014. "Semiconductor industry cycles: Explanatory factors and forecasting," Economic Modelling, Elsevier, vol. 39(C), pages 221-231.
  132. P. A. Nazarov & Kazakova, Maria, 2014. "Development of Prediction Model of Basic Budget Parameters in Russian Federation," Published Papers r90220, Russian Presidential Academy of National Economy and Public Administration.
  133. T. P. Koirala Ph.D., 2012. "Government Revenue Forecasting in Nepal," NRB Economic Review, Nepal Rastra Bank, Research Department, vol. 24(2), pages 47-60, October.
  134. Zafar, Raja Fawad & Qayyum, Abdul & Ghouri, Saghir Pervaiz, 2015. "Forecasting Inflation using Functional Time Series Analysis," MPRA Paper 67208, University Library of Munich, Germany.
  135. Luzardo-Luna, Ivan, 2020. "Labour frictions in interwar Britain: industrial reshuffling and the origin of mass unemployment," LSE Research Online Documents on Economics 105707, London School of Economics and Political Science, LSE Library.
  136. Steven M. Shugan, 2002. "Editorial: Marketing Science, Models, Monopoly Models, and Why We Need Them," Marketing Science, INFORMS, vol. 21(3), pages 223-228.
  137. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt’s exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759.
  138. Dantas, Tiago Mendes & Cyrino Oliveira, Fernando Luiz & Varela Repolho, Hugo Miguel, 2017. "Air transportation demand forecast through Bagging Holt Winters methods," Journal of Air Transport Management, Elsevier, vol. 59(C), pages 116-123.
  139. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265.
  140. 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.
  141. Najmaddin Akhundov & Nail Tahirov & Christoph H. Glock, 2022. "Optimal Scheduling of Waitstaff with Different Experience Levels at a Restaurant Chain," Interfaces, INFORMS, vol. 52(4), pages 324-343, July.
  142. T. P. Koirala, Ph.D., 2012. "Government Revenue Forecasting in Nepal," NRB Economic Review, Nepal Rastra Bank, Economic Research Department, vol. 24(2), pages 47-60, October.
  143. Jakub Dyntar & Eva Kemrová & Ivan Gros, 2010. "Simulation approach in stock control of products with sporadic demand," Ekonomika a Management, Prague University of Economics and Business, vol. 2010(3).
  144. Huddleston, Samuel H. & Porter, John H. & Brown, Donald E., 2015. "Improving forecasts for noisy geographic time series," Journal of Business Research, Elsevier, vol. 68(8), pages 1810-1818.
  145. J D Bermúdez & J V Segura & E Vercher, 2006. "Improving demand forecasting accuracy using nonlinear programming software," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 57(1), pages 94-100, January.
  146. Mustafa Akpinar & Nejat Yumusak, 2016. "Year Ahead Demand Forecast of City Natural Gas Using Seasonal Time Series Methods," Energies, MDPI, vol. 9(9), pages 1-17, September.
  147. J Keith Ord & Ralph D Snyder & Anne B Koehler & Rob J Hyndman & Mark Leeds, 2005. "Time Series Forecasting: The Case for the Single Source of Error State Space," Monash Econometrics and Business Statistics Working Papers 7/05, Monash University, Department of Econometrics and Business Statistics.
  148. Thomassey, Sébastien, 2010. "Sales forecasts in clothing industry: The key success factor of the supply chain management," International Journal of Production Economics, Elsevier, vol. 128(2), pages 470-483, December.
  149. N. Bora Keskin & Assaf Zeevi, 2017. "Chasing Demand: Learning and Earning in a Changing Environment," Mathematics of Operations Research, INFORMS, vol. 42(2), pages 277-307, May.
  150. Kyle Cattani & Warren Hausman, 2000. "Why Are Forecast Updates Often Disappointing?," Manufacturing & Service Operations Management, INFORMS, vol. 2(2), pages 119-127, July.
  151. Ferbar Tratar, Liljana, 2015. "Forecasting method for noisy demand," International Journal of Production Economics, Elsevier, vol. 161(C), pages 64-73.
  152. Nieto, María Rosa & Carmona-Benítez, Rafael Bernardo, 2018. "ARIMA + GARCH + Bootstrap forecasting method applied to the airline industry," Journal of Air Transport Management, Elsevier, vol. 71(C), pages 1-8.
  153. Marcelo Albertini & Rodrigo Mello, 2013. "Energy-based function to evaluate data stream clustering," Advances in Data Analysis and Classification, Springer;German Classification Society - Gesellschaft für Klassifikation (GfKl);Japanese Classification Society (JCS);Classification and Data Analysis Group of the Italian Statistical Society (CLADAG);International Federation of Classification Societies (IFCS), vol. 7(4), pages 435-464, December.
  154. Albrecht, Tobias & Rausch, Theresa Maria & Derra, Nicholas Daniel, 2021. "Call me maybe: Methods and practical implementation of artificial intelligence in call center arrivals’ forecasting," Journal of Business Research, Elsevier, vol. 123(C), pages 267-278.
  155. J W Taylor, 2003. "Short-term electricity demand forecasting using double seasonal exponential smoothing," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 54(8), pages 799-805, August.
  156. Kleyton da Costa & Felipe Leite Coelho da Silva & Josiane da Silva Cordeiro Coelho & Andr'e de Melo Modenesi, 2020. "A Systematic Comparison of Forecasting for Gross Domestic Product in an Emergent Economy," Papers 2010.13259, arXiv.org, revised Mar 2022.
  157. Титов В. В. & Безмельницын Д. А. & Напреева С. К., 2017. "Планирование функционирования предприятия в условиях риска и неопределенности во внешней и внутренней среде. Enterprise operation planning in the conditions of risk and uncertainty in the external and," Мир экономики и управления // Вестник НГУ. Cерия: Cоциально-экономические науки, Socionet;Новосибирский государственный университет, vol. 17(3), pages 179-191.
  158. Wei-Chiang Hong & Ping-Feng Pai, 2007. "Potential assessment of the support vector regression technique in rainfall forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 21(2), pages 495-513, February.
  159. Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
  160. Dalton Garcia Borges de Souza & Erivelton Antonio dos Santos & Francisco Tarcísio Alves Júnior & Mariá Cristina Vasconcelos Nascimento, 2021. "On Comparing Cross-Validated Forecasting Models with a Novel Fuzzy-TOPSIS Metric: A COVID-19 Case Study," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
  161. Gould, Phillip G. & Koehler, Anne B. & Ord, J. Keith & Snyder, Ralph D. & Hyndman, Rob J. & Vahid-Araghi, Farshid, 2008. "Forecasting time series with multiple seasonal patterns," European Journal of Operational Research, Elsevier, vol. 191(1), pages 207-222, November.
  162. Emmanuel Sirimal Silva & Hossein Hassani & Dag Øivind Madsen & Liz Gee, 2019. "Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends," Social Sciences, MDPI, vol. 8(4), pages 1-23, April.
  163. Castle, Jennifer L. & Clements, Michael P. & Hendry, David F., 2013. "Forecasting by factors, by variables, by both or neither?," Journal of Econometrics, Elsevier, vol. 177(2), pages 305-319.
  164. Christopher E.S. WARBURTON & Jared PEMBERTON, 2023. "Volatile Financial Conditions, Asset Prices, and Investment Decisions: Analysis of daily data of DJIA and S&P500, from January to April of 2022," Applied Econometrics and International Development, Euro-American Association of Economic Development, vol. 23(1), pages 101-124.
  165. Ord, Keith, 2004. "Charles Holt's report on exponentially weighted moving averages: an introduction and appreciation," International Journal of Forecasting, Elsevier, vol. 20(1), pages 1-3.
  166. Eren Bas & Erol Egrioglu & Ufuk Yolcu, 2021. "Bootstrapped Holt Method with Autoregressive Coefficients Based on Harmony Search Algorithm," Forecasting, MDPI, vol. 3(4), pages 1-11, November.
  167. Ayan Chattopadhyay & Somarata Chakraborty, 2019. "Market size growth survival in multi-generation technology environment: A predictive review of the Indian air-conditioner and refrigerator industry," Asian Journal of Empirical Research, Asian Economic and Social Society, vol. 9(5), pages 132-146, May.
  168. Bermudez, J.D. & Segura, J.V. & Vercher, E., 2006. "A decision support system methodology for forecasting of time series based on soft computing," Computational Statistics & Data Analysis, Elsevier, vol. 51(1), pages 177-191, November.
  169. Cheng-Hong Yang & Bo-Hong Chen & Chih-Hsien Wu & Kuo-Chang Chen & Li-Yeh Chuang, 2022. "Deep Learning for Forecasting Electricity Demand in Taiwan," Mathematics, MDPI, vol. 10(14), pages 1-19, July.
  170. Silva, Emmanuel Sirimal & Hassani, Hossein & Heravi, Saeed & Huang, Xu, 2019. "Forecasting tourism demand with denoised neural networks," Annals of Tourism Research, Elsevier, vol. 74(C), pages 134-154.
  171. Avgustin Milanov, 2020. "Forecasting Of Some Key Indicators Of The Rfi And Rfp Processes Of The Bulgarian Mobile Telecommunication Operators," Economics & Law, Faculty of Economics, SOUTH-WEST UNIVERSITY "NEOFIT RILSKI", BLAGOEVGRAD, vol. 2(2), pages 62-70.
  172. Oscar Trull & Juan Carlos García-Díaz & Alicia Troncoso, 2020. "Initialization Methods for Multiple Seasonal Holt–Winters Forecasting Models," Mathematics, MDPI, vol. 8(2), pages 1-16, February.
  173. Nela Vlahinic & Pavle Jakovac, 2014. "Revisiting the Energy Consumption-Growth Nexus for Croatia: New Evidence from a Multivariate Framework Analysis," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 8(4), December.
  174. Anis Chariri & Indira Januarti, 2017. "Audit Committee Characteristics and Integrated Reporting:Empirical Study of Companies Listed on the Johannesburg Stock Exchange," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 305-318.
  175. Michael J. O'Neill & Zhangxin Liu & Tom Smith, 2017. "Fund Volatility Index using equity market state prices," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 57(3), pages 837-853, September.
  176. Elena Ganón & Ina Tiscordio, 2007. "Un análisis de variables fiscales del Gobierno Central del Uruguay para el período 1989-2006," Documentos de trabajo 2007005, Banco Central del Uruguay.
  177. Lahiri, Kajal & Yin, Yimeng, 2024. "Seasonality in U.S. disability applications, labor market, and the pandemic echoes," Labour Economics, Elsevier, vol. 87(C).
  178. Oscar Trull & Angel Peiró-Signes & J. Carlos García-Díaz, 2019. "Electricity Forecasting Improvement in a Destination Using Tourism Indicators," Sustainability, MDPI, vol. 11(13), pages 1-16, July.
  179. Thiago Rezende dos Santos & Enrico A. Colosimo, 2015. "A modified approximate method for analysis of degradation data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 42(6), pages 1322-1331, June.
  180. Oscar Trull & J. Carlos Garc'ia-D'iaz & Angel Peir'o-Signes, 2024. "mshw, a forecasting library to predict short-term electricity demand based on multiple seasonal Holt-Winters," Papers 2402.10982, arXiv.org.
  181. Kusters, Ulrich & McCullough, B.D. & Bell, Michael, 2006. "Forecasting software: Past, present and future," International Journal of Forecasting, Elsevier, vol. 22(3), pages 599-615.
  182. Lila, Maurício Franca & Meira, Erick & Cyrino Oliveira, Fernando Luiz, 2022. "Forecasting unemployment in Brazil: A robust reconciliation approach using hierarchical data," Socio-Economic Planning Sciences, Elsevier, vol. 82(PB).
  183. Dicembrino, Claudio & Trovato, Giovanni, 2013. "Structural Breaks, Price and Income Elasticity, and Forecast of the Monthly Italian Electricity Demand," MPRA Paper 47653, University Library of Munich, Germany.
  184. Trond Husby & Hans Visser, 2021. "Short- to medium-run forecasting of mobility with dynamic linear models," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 45(28), pages 871-902.
  185. George E. P. Box & Steven Hillmer & George C. Tiao, 1979. "Analysis and Modeling of Seasonal Time Series," NBER Chapters, in: Seasonal Analysis of Economic Time Series, pages 309-346, National Bureau of Economic Research, Inc.
  186. McKenzie, Eddie & Gardner Jr., Everette S., 2010. "Damped trend exponential smoothing: A modelling viewpoint," International Journal of Forecasting, Elsevier, vol. 26(4), pages 661-665, October.
  187. Melina Dritsaki & Chaido Dritsaki, 2022. "Comparison of HP Filter and the Hamilton’s Regression," Mathematics, MDPI, vol. 10(8), pages 1-18, April.
  188. Krembsler, Jonas & Spiegelberg, Sandra & Hasenfelder, Richard & Kämpf, Nicki Lena & Winter, Thomas & Winter, Nicola & Knappe, Robert, 2024. "Fare revenue forecast in public transport: A comparative case study," Research in Transportation Economics, Elsevier, vol. 105(C).
  189. Job Nmadu & Ezekiel Yisa & Usman Mohammed & Halima Sallawu & Yebosoko Nmadu & Sokoyami Nmadu, 2022. "Structural Analysis and Forecast of Nigerian Monthly Inflation Movement between 1996 and 2022," RAIS Conference Proceedings 2022-2024 0211, Research Association for Interdisciplinary Studies.
  190. Irene Mariñas-Collado & Ana E. Sipols & M. Teresa Santos-Martín & Elisa Frutos-Bernal, 2022. "Clustering and Forecasting Urban Bus Passenger Demand with a Combination of Time Series Models," Mathematics, MDPI, vol. 10(15), pages 1-16, July.
  191. Tryggvi Jónsson & Pierre Pinson & Henrik Aa. Nielsen & Henrik Madsen, 2014. "Exponential Smoothing Approaches for Prediction in Real-Time Electricity Markets," Energies, MDPI, vol. 7(6), pages 1-23, June.
  192. Godfrey, Gregory A. & Powell, Warren B., 2000. "Adaptive estimation of daily demands with complex calendar effects for freight transportation," Transportation Research Part B: Methodological, Elsevier, vol. 34(6), pages 451-469, August.
  193. Pim Ouwehand & Rob J. Hyndman & Ton G. de Kok & Karel H. van Donselaar, 2007. "A state space model for exponential smoothing with group seasonality," Monash Econometrics and Business Statistics Working Papers 7/07, Monash University, Department of Econometrics and Business Statistics.
  194. Zhanarys S. Raimbekov & Bakyt U. Syzdykbayeva & Kamshat P. Mussina & Luiza P. Moldashbayeva & Bakytzhamal A. Zhumataeva, 2017. "The Study of the Logistics Development Effectiveness in the Eurasian Economic Union Countries and Measures to Improve it," European Research Studies Journal, European Research Studies Journal, vol. 0(4B), pages 260-276.
  195. Eunjoo Yang & Hyun Woo Park & Yeon Hwa Choi & Jusim Kim & Lkhagvadorj Munkhdalai & Ibrahim Musa & Keun Ho Ryu, 2018. "A Simulation-Based Study on the Comparison of Statistical and Time Series Forecasting Methods for Early Detection of Infectious Disease Outbreaks," IJERPH, MDPI, vol. 15(5), pages 1-18, May.
  196. Tashman, Leonard J. & Kruk, Joshua M., 1996. "The use of protocols to select exponential smoothing procedures: A reconsideration of forecasting competitions," International Journal of Forecasting, Elsevier, vol. 12(2), pages 235-253, June.
  197. Jennifer Castle & David Hendry & Oleg Kitov, 2013. "Forecasting and Nowcasting Macroeconomic Variables: A Methodological Overview," Economics Series Working Papers 674, University of Oxford, Department of Economics.
  198. Li, Yanting & Su, Yan & Shu, Lianjie, 2014. "An ARMAX model for forecasting the power output of a grid connected photovoltaic system," Renewable Energy, Elsevier, vol. 66(C), pages 78-89.
  199. R. Sarma & S. K. Singh, 2022. "A Comparative Study of Data-driven Models for Groundwater Level Forecasting," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 36(8), pages 2741-2756, June.
  200. Fabian Schäfer & Manuel Walther & Dominik G. Grimm & Alexander Hübner, 2023. "Combining machine learning and optimization for the operational patient-bed assignment problem," Health Care Management Science, Springer, vol. 26(4), pages 785-806, December.
  201. Jennifer L. Castle & Jurgen A. Doornik & David F. Hendry, 2021. "Forecasting Principles from Experience with Forecasting Competitions," Forecasting, MDPI, vol. 3(1), pages 1-28, February.
  202. Ayala, Astrid & Blazsek, Szabolcs, 2013. "Structural breaks in public finances in Central and Eastern European countries," Economic Systems, Elsevier, vol. 37(1), pages 45-60.
  203. Corberán-Vallet, Ana & Bermúdez, José D. & Vercher, Enriqueta, 2011. "Forecasting correlated time series with exponential smoothing models," International Journal of Forecasting, Elsevier, vol. 27(2), pages 252-265, April.
  204. P. A. Nazarov & Kazakova, Maria, 2014. "Methodological Principles of Prediction of Tax Revenues of Budgetary System," Published Papers r90219, Russian Presidential Academy of National Economy and Public Administration.
  205. Ralph D. Snyder & Anne B. Koehler & Rob J. Hyndman & J. Keith Ord, 2002. "Exponential Smoothing for Inventory Control: Means and Variances of Lead-Time Demand," Monash Econometrics and Business Statistics Working Papers 3/02, Monash University, Department of Econometrics and Business Statistics.
  206. Zhen Zeng & Rachneet Kaur & Suchetha Siddagangappa & Saba Rahimi & Tucker Balch & Manuela Veloso, 2023. "Financial Time Series Forecasting using CNN and Transformer," Papers 2304.04912, arXiv.org.
  207. Haberleitner, Helmut & Meyr, Herbert & Taudes, Alfred, 2010. "Implementation of a demand planning system using advance order information," International Journal of Production Economics, Elsevier, vol. 128(2), pages 518-526, December.
  208. Ralph D. Snyder, 2004. "Exponential Smoothing: A Prediction Error Decomposition Principle," Monash Econometrics and Business Statistics Working Papers 15/04, Monash University, Department of Econometrics and Business Statistics.
  209. Hansen, Bjørn Gunnar, 2015. "Different methods to forecast milk delivery to dairy: a comparison for forecasting," International Journal of Agricultural Management, Institute of Agricultural Management, vol. 4(3), April.
  210. Judy L Klein, 2015. "The Cold War Hot House for Modeling Strategies at the Carnegie Institute of Technology," Working Papers Series 19, Institute for New Economic Thinking.
  211. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
  212. Felipe Santos‐Marquez, 2022. "Spatial beta‐convergence forecasting models: Evidence from municipal homicide rates in Colombia," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(2), pages 294-302, March.
  213. Maia, André Luis Santiago & de Carvalho, Francisco de A.T., 2011. "Holt's exponential smoothing and neural network models for forecasting interval-valued time series," International Journal of Forecasting, Elsevier, vol. 27(3), pages 740-759, July.
  214. Zhou, Shenghan & Hu, Chen & Qiao, Xiaoduo & Chang, Wenbing, 2016. "A forecasting method for Chinese civil planes attendance rate based on vague sets," Chaos, Solitons & Fractals, Elsevier, vol. 89(C), pages 518-526.
  215. Babai, M.Z. & Ali, M.M. & Boylan, J.E. & Syntetos, A.A., 2013. "Forecasting and inventory performance in a two-stage supply chain with ARIMA(0,1,1) demand: Theory and empirical analysis," International Journal of Production Economics, Elsevier, vol. 143(2), pages 463-471.
  216. Jiayun Wang & Shanshan Wu & Qingwei Jin & Yijun Wang & Can Chen, 2024. "Identifying Popular Products at an Early Stage of Sales Season for Apparel Industry," Interfaces, INFORMS, vol. 54(3), pages 282-296, May.
  217. Kyriazi, Foteini & Thomakos, Dimitrios D. & Guerard, John B., 2019. "Adaptive learning forecasting, with applications in forecasting agricultural prices," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1356-1369.
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