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Forecasting seasonals and trends by exponentially weighted moving averages
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- Pantelis Agathangelou & Demetris Trihinas & Ioannis Katakis, 2020. "A Multi-Factor Analysis of Forecasting Methods: A Study on the M4 Competition," Data, MDPI, vol. 5(2), pages 1-24, April.
- 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.
- 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.
- 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.
- Yang, Dazhi & Sharma, Vishal & Ye, Zhen & Lim, Lihong Idris & Zhao, Lu & Aryaputera, Aloysius W., 2015. "Forecasting of global horizontal irradiance by exponential smoothing, using decompositions," Energy, Elsevier, vol. 81(C), pages 111-119.
- Joseph Ross, 2021. "Stationarity Statistics on Rolling Windows," Computational Economics, Springer;Society for Computational Economics, vol. 57(2), pages 655-691, February.
- Andrew Muhammad & Amanda M. Countryman, 2019.
"In Vino ‘No’ Veritas: impacts of fraud on wine imports in China,"
Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), pages 742-758, October.
- Muhammad, Andrew & Countryman, Amanda M., 2019. "In Vino ‘No’ Veritas: impacts of fraud on wine imports in China," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 63(4), October.
- Yuxin Zhang & Yifei Yang & Xiaosi Li & Zijing Yuan & Yuki Todo & Haichuan Yang, 2023. "A Dendritic Neuron Model Optimized by Meta-Heuristics with a Power-Law-Distributed Population Interaction Network for Financial Time-Series Forecasting," Mathematics, MDPI, vol. 11(5), pages 1-20, March.
- Sanders, Dwight R. & Manfredo, Mark R., 2006.
"Forecasting Basis Levels in the Soybean Complex: A Comparison of Time Series Methods,"
Journal of Agricultural and Applied Economics, Cambridge University Press, vol. 38(3), pages 513-523, December.
- Sanders, Dwight R. & Manfredo, Mark R., 2006. "Forecasting Basis Levels in the Soybean Complex: A Comparison of Time Series Methods," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 38(3), pages 1-11, December.
- Simona Mikšíková & David Ulčák & František Kuda, 2022. "Analysis of Malfunctions in Selected Parking Systems in the Czech Republic," Sustainability, MDPI, vol. 14(3), pages 1-10, February.
- Zhou, Huimin & Dang, Yaoguo & Yang, Yingjie & Wang, Junjie & Yang, Shaowen, 2023. "An optimized nonlinear time-varying grey Bernoulli model and its application in forecasting the stock and sales of electric vehicles," Energy, Elsevier, vol. 263(PC).
- Hu, Yuntong & Xiao, Fuyuan, 2022. "A novel method for forecasting time series based on directed visibility graph and improved random walk," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 594(C).
- Xianbo Li, 2022. "Sequence Model and Prediction for Sustainable Enrollments in Chinese Universities," Sustainability, MDPI, vol. 15(1), pages 1-25, December.
- 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.
- Agustín A. Sánchez de la Nieta & Virginia González & Javier Contreras, 2016. "Portfolio Decision of Short-Term Electricity Forecasted Prices through Stochastic Programming," Energies, MDPI, vol. 9(12), pages 1-19, December.
- Singh Doorga, Jay Rovisham & Dhurmea, Kumar Ram & Rughooputh, Soonil & Boojhawon, Ravindra, 2019. "Forecasting mesoscale distribution of surface solar irradiation using a proposed hybrid approach combining satellite remote sensing and time series models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 104(C), pages 69-85.
- Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2015. "Forecasting implied volatility indices worldwide: A new approach," MPRA Paper 72084, University Library of Munich, Germany.
- Ralph D. Snyder & J. Keith Ord, 2009. "Exponential Smoothing and the Akaike Information Criterion," Monash Econometrics and Business Statistics Working Papers 4/09, Monash University, Department of Econometrics and Business Statistics.
- Liu, Che & Sun, Bo & Zhang, Chenghui & Li, Fan, 2020. "A hybrid prediction model for residential electricity consumption using holt-winters and extreme learning machine," Applied Energy, Elsevier, vol. 275(C).
- Gardner, Everette S., 2015. "Conservative forecasting with the damped trend," Journal of Business Research, Elsevier, vol. 68(8), pages 1739-1741.
- 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).
- Gardner, Everette Shaw & Acar, Yavuz, 2016. "The forecastability quotient reconsidered," International Journal of Forecasting, Elsevier, vol. 32(4), pages 1208-1211.
- Hossein Yousefi & Mohammad Hasan Ghodusinejad & Armin Ghodrati, 2022. "Multi-Criteria Future Energy System Planning and Analysis for Hot Arid Areas of Iran," Energies, MDPI, vol. 15(24), pages 1-25, December.
- 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.
- 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).
- Wei Fang & Yu Sha & Victor S. Sheng, 2022. "Survey on the Application of Artificial Intelligence in ENSO Forecasting," Mathematics, MDPI, vol. 10(20), pages 1-22, October.
- Ching-Chih Chang & Yu-Wei Chang & Po-Chien Huang, 2022. "Effects of the INDC and GGRMA Regulations on the Impact of PM 2.5 Particle Emissions on Maritime Ports: A Study of Human Health and Environmental Costs," Sustainability, MDPI, vol. 14(10), pages 1-15, May.
- 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.
- Masuda, Tadayoshi & Goldsmith, Peter D., 2012. "China's Meat and Egg Production and Soybean Meal Demand for Feed: An Elasticity Analysis and Long-Term Projections," International Food and Agribusiness Management Review, International Food and Agribusiness Management Association, vol. 15(3), pages 1-20, September.
- Tianxiang Zhan & Fuyuan Xiao, 2021. "A Fast Evidential Approach for Stock Forecasting," Papers 2104.05204, arXiv.org, revised Jul 2021.
- 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.
- 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.
- Islam, Samiul & Amin, Saman Hassanzadeh & Wardley, Leslie J., 2021. "Machine learning and optimization models for supplier selection and order allocation planning," International Journal of Production Economics, Elsevier, vol. 242(C).
- Hong Wang & Guangyu Long & Jianxing Liao & Yan Xu & Yan Lv, 2022. "A new hybrid method for establishing point forecasting, interval forecasting, and probabilistic forecasting of landslide displacement," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 111(2), pages 1479-1505, March.
- 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).
- Rong Zhang & Baabak Ashuri & Yong Deng, 2017. "A novel method for forecasting time series based on fuzzy logic and visibility graph," 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. 11(4), pages 759-783, December.
- Kelachukwu J. Iheanetu, 2022. "Solar Photovoltaic Power Forecasting: A Review," Sustainability, MDPI, vol. 14(24), pages 1-31, December.
- 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.
- Xue-Bo Jin & Wei-Zhen Zheng & Jian-Lei Kong & Xiao-Yi Wang & Yu-Ting Bai & Ting-Li Su & Seng Lin, 2021. "Deep-Learning Forecasting Method for Electric Power Load via Attention-Based Encoder-Decoder with Bayesian Optimization," Energies, MDPI, vol. 14(6), pages 1-18, March.
- Dyna Heng & Anna Ivanova & Rodrigo Mariscal & Ms. Uma Ramakrishnan & Joyce Wong, 2016. "Advancing Financial Development in Latin America and the Caribbean," IMF Working Papers 2016/081, International Monetary Fund.
- Lazos, Dimitris & Sproul, Alistair B. & Kay, Merlinde, 2014. "Optimisation of energy management in commercial buildings with weather forecasting inputs: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 39(C), pages 587-603.
- Kim, Sungil & Kim, Heeyoung, 2016. "A new metric of absolute percentage error for intermittent demand forecasts," International Journal of Forecasting, Elsevier, vol. 32(3), pages 669-679.
- Simona Mikšíková & David Ulčák & Dagmar Kutá, 2023. "Assessment of Automated Parking Garage Services as a Means to Sustainable Traffic Development in a Mid-Sized City," Sustainability, MDPI, vol. 15(3), pages 1-15, January.
- Zhen Zeng & Tucker Balch & Manuela Veloso, 2021. "Deep Video Prediction for Time Series Forecasting," Papers 2102.12061, arXiv.org, revised Nov 2021.
- Theodosiou, Marina, 2011. "Forecasting monthly and quarterly time series using STL decomposition," International Journal of Forecasting, Elsevier, vol. 27(4), pages 1178-1195, October.
- Kopnova, Elena & Rodionova, Liliya, 2020. "Globalization and socio-economic development in Russia," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 60, pages 80-101.
- 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.
- Stupen R.M., 2018. "Forecast scenarios for the development of agricultural land market," Balanced Nature Using, Institute of agroecology and environmental management, vol. 10(4), pages 96-105, December.
- 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.
- Kang, Wensheng & Ratti, Ronald A. & Vespignani, Joaquin L., 2016. "The implications of monetary expansion in China for the US dollar," Journal of Asian Economics, Elsevier, vol. 46(C), pages 71-84.
- 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.
- Erjiang E & Ming Yu & Xin Tian & Ye Tao, 2022. "Dynamic Model Selection Based on Demand Pattern Classification in Retail Sales Forecasting," Mathematics, MDPI, vol. 10(17), pages 1-16, September.
- 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.
- 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.
- Stefan Steinerberger & Aleh Tsyvinski, 2020.
"On Vickrey's Income Averaging,"
Papers
2004.06289, arXiv.org.
- Stefan Steinerberger & Aleh Tsyvinski, 2020. "On Vickrey’s Income Averaging," NBER Working Papers 27024, National Bureau of Economic Research, Inc.
- Kim, Yochan & Park, Jinkyun & Jung, Wondea, 2017. "A quantitative measure of fitness for duty and work processes for human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 595-601.
- Tomasz Małysa & Bożena Gajdzik, 2020. "Predictive Models of Accidents at Work in the Steel Sector as a Framework for Sustainable Safety," Energies, MDPI, vol. 14(1), pages 1-20, December.
- 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).
- Xi Wu & Adam Blake, 2023. "The Impact of the COVID-19 Crisis on Air Travel Demand: Some Evidence From China," SAGE Open, , vol. 13(1), pages 21582440231, January.
- Ahmad M Awajan & Mohd Tahir Ismail & S AL Wadi, 2018. "Improving forecasting accuracy for stock market data using EMD-HW bagging," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-20, July.
- Tuo Sun & Shihao Zhu & Ruochen Hao & Bo Sun & Jiemin Xie, 2022. "Traffic Missing Data Imputation: A Selective Overview of Temporal Theories and Algorithms," Mathematics, MDPI, vol. 10(14), pages 1-22, July.
- Linlin Zhao & Zhansheng Liu & Jasper Mbachu, 2019. "Energy Management through Cost Forecasting for Residential Buildings in New Zealand," Energies, MDPI, vol. 12(15), pages 1-24, July.
- Wolfram Rozas & Rafael Pastor-Vargas & Angel Miguel García-Vico & José Carpio, 2023. "Consumption–Production Profile Categorization in Energy Communities," Energies, MDPI, vol. 16(19), pages 1-27, October.
- Posch, Konstantin & Truden, Christian & Hungerländer, Philipp & Pilz, Jürgen, 2022. "A Bayesian approach for predicting food and beverage sales in staff canteens and restaurants," International Journal of Forecasting, Elsevier, vol. 38(1), pages 321-338.
- Guo-hua Ye & Mirxat Alim & Peng Guan & De-sheng Huang & Bao-sen Zhou & Wei Wu, 2021. "Improving the precision of modeling the incidence of hemorrhagic fever with renal syndrome in mainland China with an ensemble machine learning approach," PLOS ONE, Public Library of Science, vol. 16(3), pages 1-13, March.
- Yumin Li & Ruiqi Yang & Xiaoman Wang & Jiaming Zhu & Nan Song, 2023. "Carbon Price Combination Forecasting Model Based on Lasso Regression and Optimal Integration," Sustainability, MDPI, vol. 15(12), pages 1-26, June.
- Achal Bassamboo & Rouba Ibrahim, 2021. "A General Framework to Compare Announcement Accuracy: Static vs. LES-Based Announcement," Management Science, INFORMS, vol. 67(7), pages 4191-4208, July.
- Gardner, Everette Jr., 2006. "Exponential smoothing: The state of the art--Part II," International Journal of Forecasting, Elsevier, vol. 22(4), pages 637-666.
- Svetunkov, Ivan & Kourentzes, Nikolaos, 2015. "Complex Exponential Smoothing," MPRA Paper 69394, University Library of Munich, Germany.
- Sabaj, Ernil & Kahveci, Mustafa, 2018. "Forecasting tax revenues in an emerging economy: The case of Albania," MPRA Paper 84404, University Library of Munich, Germany.
- Andrzej Tytko & Grzegorz Olszyna & Grzegorz Kocór & Mariusz Szot, 2023. "Some Stochastic Aspects of Safety Work of Steel Wire Ropes Used in Mining-Shaft Hoists," Sustainability, MDPI, vol. 15(9), pages 1-13, May.
- 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.
- Jan G. De Gooijer & Rob J. Hyndman, 2005. "25 Years of IIF Time Series Forecasting: A Selective Review," Monash Econometrics and Business Statistics Working Papers 12/05, Monash University, Department of Econometrics and Business Statistics.
- Acar, Yavuz & Gardner, Everette S., 2012. "Forecasting method selection in a global supply chain," International Journal of Forecasting, Elsevier, vol. 28(4), pages 842-848.
- Wensheng Kang & Ronald A. Ratti & Joaquin L. Vespignani, 2016.
"The implications of liquidity expansion in China for the US dollar,"
Globalization Institute Working Papers
264, Federal Reserve Bank of Dallas.
- Kang, Wensheng & Ratti, Ronald. A. & Vespignani, Joaquin, 2016. "The implications of liquidity expansion in China for the US dollar," Working Papers 2016-02, University of Tasmania, Tasmanian School of Business and Economics.
- Wensheng Kang & Ronald A. Ratti & Joaquin L. Vespignani, 2016. "The implications of liquidity expansion in China for the US dollar," CAMA Working Papers 2016-05, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
- Ahmed Belhadjayed & Grégoire Loeper & Frédéric Abergel, 2016. "Forecasting Trends With Asset Prices," Post-Print hal-01512431, HAL.
- Karzan Mahdi Ghafour & Abdulqadir Rahomee Ahmed Aljanabi, 2023. "The role of forecasting in preventing supply chain disruptions during the COVID-19 pandemic: a distributor-retailer perspective," Operations Management Research, Springer, vol. 16(2), pages 780-793, June.
- Mikhail Zymbler & Elena Ivanova, 2021. "Matrix Profile-Based Approach to Industrial Sensor Data Analysis Inside RDBMS," Mathematics, MDPI, vol. 9(17), pages 1-19, September.
- Jean‐Christophe Delfim & Martin Hoesli, 2021.
"Robust desmoothed real estate returns,"
Real Estate Economics, American Real Estate and Urban Economics Association, vol. 49(1), pages 75-105, March.
- Jean-Christophe Delfim & Martin Hoesli, 2019. "Robust Desmoothed Real Estate Returns," Swiss Finance Institute Research Paper Series 19-32, Swiss Finance Institute.
- Fieger, Peter & Rice, John, 2016. "Modelling Chinese Inbound Tourism Arrivals into Christchurch," MPRA Paper 75468, University Library of Munich, Germany.
- Gregor Hendel & Daniel Anderson & Pierre Le Bodic & Marc E. Pfetsch, 2022. "Estimating the Size of Branch-and-Bound Trees," INFORMS Journal on Computing, INFORMS, vol. 34(2), pages 934-952, March.
- Hanns de la Fuente-Mella & Claudio Elórtegui-Gómez & Benito Umaña-Hermosilla & Marisela Fonseca-Fuentes & Gonzalo Ríos-Vásquez, 2023. "Stochastic Approaches Systems to Predictive and Modeling Chilean Wildfires," Mathematics, MDPI, vol. 11(20), pages 1-23, October.
- Ollech, Daniel, 2018. "Seasonal adjustment of daily time series," Discussion Papers 41/2018, Deutsche Bundesbank.
- Koopman, Siem Jan & Ooms, Marius, 2006.
"Forecasting daily time series using periodic unobserved components time series models,"
Computational Statistics & Data Analysis, Elsevier, vol. 51(2), pages 885-903, November.
- Siem Jan Koopman & Marius Ooms, 2004. "Forecasting Daily Time Series using Periodic Unobserved Components Time Series Models," Tinbergen Institute Discussion Papers 04-135/4, Tinbergen Institute.
- 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.
- 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.
- Fang-Fang Li & Zhi-Yu Wang & Xiao Zhao & En Xie & Jun Qiu, 2019. "Decomposition-ANN Methods for Long-Term Discharge Prediction Based on Fisher’s Ordered Clustering with MESA," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 33(9), pages 3095-3110, July.
- Mirna Patricia Ponce-Flores & Jesús David Terán-Villanueva & Salvador Ibarra-Martínez & José Antonio Castán-Rocha, 2023. "Generalized Pandemic Model with COVID-19 for Early-Stage Infection Forecasting," Mathematics, MDPI, vol. 11(18), pages 1-18, September.
- repec:wai:econwp:13/15 is not listed on IDEAS
- Leandro Pereira & Carlos Jerónimo & Mariana Sempiterno & Renato Lopes da Costa & Álvaro Dias & Nélson António, 2021. "Events and Festivals Contribution for Local Sustainability," Sustainability, MDPI, vol. 13(3), pages 1-8, February.
- Dinesh Reddy Vangumalli & Konstantinos Nikolopoulos & Konstantia Litsiou, 2019. "Clustering, Forecasting and Cluster Forecasting: using k-medoids, k-NNs and random forests for cluster selection," Working Papers 19016, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
- 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.
- Kung-Sik Chan & Simone Giannerini & Greta Goracci & Howell Tong, 2020. "Testing for threshold regulation in presence of measurement error with an application to the PPP hypothesis," Papers 2002.09968, arXiv.org, revised Nov 2021.
- 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.
- 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.
- 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.
- Ferbar Tratar, Liljana & Strmčnik, Ervin, 2016. "The comparison of Holt–Winters method and Multiple regression method: A case study," Energy, Elsevier, vol. 109(C), pages 266-276.
- D. Th. Vezeris & C. J. Schinas & Th. S. Kyrgos & V. A. Bizergianidou & I. P. Karkanis, 2020. "Optimization of Backtesting Techniques in Automated High Frequency Trading Systems Using the d-Backtest PS Method," Computational Economics, Springer;Society for Computational Economics, vol. 56(4), pages 975-1054, December.
- Xin Gao & Xiaobing Li & Bing Zhao & Weijia Ji & Xiao Jing & Yang He, 2019. "Short-Term Electricity Load Forecasting Model Based on EMD-GRU with Feature Selection," Energies, MDPI, vol. 12(6), pages 1-18, March.
- Daud Ali Aser & Esin Firuzan, 2022. "Improving Forecast Accuracy Using Combined Forecasts with Regard to Structural Breaks and ARCH Innovations," EKOIST Journal of Econometrics and Statistics, Istanbul University, Faculty of Economics, vol. 0(37), pages 1-25, December.
- Degiannakis, Stavros & Filis, George & Hassani, Hossein, 2018. "Forecasting global stock market implied volatility indices," Journal of Empirical Finance, Elsevier, vol. 46(C), pages 111-129.
- Steinbuks, Jevgenijs, 2019. "Assessing the accuracy of electricity production forecasts in developing countries," International Journal of Forecasting, Elsevier, vol. 35(3), pages 1175-1185.
- 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.
- Moser, Philipp & Isaksson, Olov H.D. & Seifert, Ralf W., 2017. "Inventory dynamics in process industries: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 191(C), pages 253-266.
- Jang-yeop Kim & Kyung Sup Kim, 2018. "Integrated Model of Economic Generation System Expansion Plan for the Stable Operation of a Power Plant and the Response of Future Electricity Power Demand," Sustainability, MDPI, vol. 10(7), pages 1-27, July.
- Arnab Mitra & Arnav Jain & Avinash Kishore & Pravin Kumar, 2022. "A Comparative Study of Demand Forecasting Models for a Multi-Channel Retail Company: A Novel Hybrid Machine Learning Approach," SN Operations Research Forum, Springer, vol. 3(4), pages 1-22, December.
- Amani Almohaimeed & Jochen Einbeck & Najla Qarmalah & Hanan Alkhidhr, 2022. "Using Random Effect Models to Produce Robust Estimates of Death Rates in COVID-19 Data," IJERPH, MDPI, vol. 19(22), pages 1-13, November.
- 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.
- Rameshwar Garg & Shriya Barpanda & Girish Rao Salanke N S & Ramya S, 2022. "Machine Learning Algorithms for Time Series Analysis and Forecasting," Papers 2211.14387, arXiv.org.
- Lu, Emiao & Handl, Julia & Xu, Dong-ling, 2018. "Determining analogies based on the integration of multiple information sources," International Journal of Forecasting, Elsevier, vol. 34(3), pages 507-528.
- 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.
- 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.
- 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.
- Yavuz Acar, 2014. "Forecasting Method Selection Based on Operational Performance," Bogazici Journal, Review of Social, Economic and Administrative Studies, Bogazici University, Department of Economics, vol. 28(1), pages 95-114.
- 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.
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