Journal Papers

KLLAB members (bold texts); equal-contributed authors (#); corresponding author (*)

  1. 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, Jethro Browell, Claudio Carnevale, Jennifer L. Castle, Pasquale Cirillo, Michael P. Clements, Clara Cordeiro, Fernando Luiz Cyrino Oliveira, Shari De Baets, Alexander Dokumentov, Joanne Ellison, Piotr Fiszeder, Philip Hans Franses, David T. Frazier, Michael Gilliland, M. Sinan Gönül, Paul Goodwin, Luigi Grossi, Yael Grushka-Cockayne, Mariangela Guidolin, Massimo Guidolin, Ulrich Gunter, Xiaojia Guo, Renato Guseo, Nigel Harvey, David F. Hendry, Ross Hollyman, Tim Januschowski, Jooyoung Jeon, Victor Richmond R. Jose, Yanfei Kang, Anne B. Koehler, Stephan Kolassa, Nikolaos Kourentzes, Sonia Leva, Feng Li, Konstantia Litsiou, Spyros Makridakis, Gael M. Martin, Andrew B. Martinez, Sheik Meeran, Theodore Modis, Konstantinos Nikolopoulos, Dilek Önkal, Alessia Paccagnini, Anastasios Panagiotelis, Ioannis Panapakidis, Jose M. Pavía, Manuela Pedio, Diego J. Pedregal, Pierre Pinson, Patrícia Ramos, David E. Rapach, J. James Reade, Bahman Rostami-Tabar, Michał Rubaszek, Georgios Sermpinis, Han Lin Shang, Evangelos Spiliotis, Aris A. Syntetos, Priyanga Dilini Talagala, Thiyanga S. Talagala, Len Tashman, Dimitrios Thomakos, Thordis Thorarinsdottir, Ezio Todini, Juan Ramón Trapero Arenas, Xiaoqian Wang, Robert L. Winkler, Alisa Yusupova, & Florian Zie (2021). Forecasting: theory and practice. International Journal of Forecasting (In Press)
  2. Yanfei KangWei Cao, Fotios Petropoulos & Feng Li* (2021). Forecast with Forecasts: Diversity MattersEuropean Journal of Operational Research. (In Press)
  3. Xixi Li#, Yun Bai#, Yanfei Kang* (2021). Exploring the social influence of Kaggle virtual community on the M5 competition. International Journal of Forecasting. In press.
  4. Evangelos Theodorou#, Shengjie Wang#Yanfei Kang*, Evangelos Spiliotis, Spyros Makridakis, Vassilios Assimakopoulos (2021). Exploring the representativeness of the M5 competition data. International Journal of Forecasting. (in press).
  5. Rui Pan, Tunan Ren, Baishan Guo, Feng Li, Guodong Li and Hansheng Wang (2021). A Note on Distributed Quantile Regression by Pilot Sampling and One-Step UpdatingJournal of Business and Economic Statistics. (in press).
  6. Thiyanga S. Talagala, Feng LiYanfei Kang* (2021). FFORMPP: Feature-based forecast model performance predictionInternational Journal of Forecasting. (in press)
  7. Kasun Bandara, Hansika Hewamalage, Yuan-Hao Liu, Yanfei Kang, Christoph Bergmeir (2021). Improving the Accuracy of Global Forecasting Models using Time Series Data AugmentationPattern Recognition. (in press)
  8. Xuening Zhu, Feng Li*, & Hansheng Wang (2021). Least-square approximation for a distributed system. Journal of Computational and Graphical Statistics. (in press).
  9. Xiaoqian Wang, Yanfei Kang, Fotios Petropoulos, & Feng Li* (2021). The uncertainty estimation of feature-based forecast combinations, Journal of the Operational Research Society. (in press).
  10. Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li*, & Vassilios Assimakopoulo (2021). Déjà vu: A data-centric forecasting approach through time series cross-similarityJournal of Business Research. 132(2021):719-731.
  11. Megan GJaneway, Xiang Zhao, Max Rosenthaler, Yi Zuo, Kumar Balasubramaniyane, Michael Poulson, Miriam Neufeld, Jeffrey J. Siracuse, Courtney E. Takahashif, Lisa, Allee, Tracey Dechert, Peter A Burke, Feng Li, and Bindu Kalesan (2021). Clinical diagnostic phenotypes in hospitalizations due to self-inflicted firearm injuryJournal of Affective Disorders 278(1):172-180.
  12. Yitian Chen, Yanfei Kang*, Yixiong Chen, Zizhuo Wang (2020). Probabilistic Forecasting with Temporal Convolutional Neural NetworkNeurocomputing 399: 491-501.
  13. Xixi Li, Yanfei Kang,  & Feng Li* (2020). Forecasting with time series imagingExpert Systems with Applications 160: 113680.
  14. Yanfei Kang, Rob J Hyndman,  & Feng Li* (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristicsStatistical Analysis and Data Mining 13(4): 354-376.
  15. Chengcheng Hao, Feng Li,  & Dietrich von Rosen (2020). A Bilinear Reduced Rank ModelIn Jianqing Fan and Jianxin Pan (eds.), Contemporary Experimental Design, Multivariate Analysis and Data Mining, Springer.
  16. Bindu Kalesan, Siran Zhao, Michael Poulson, Miriam Neufeld, Tracey Dechert, Jeffrey J Siracuse, Yi Zuo, and Feng Li (2020). Intersections between firearm suicide, drug mortality and economic dependency in rural AmericaJournal of Surgical Research. 256, pp 96-102. Journal’s Cover Paper.
  17. Hannah M Bailey, Yi Zuo, Feng Li, Jae Min, Krishna Vaddiparti, Mattia Prosperi, Jeffrey Fagan, Sandro Galea,  & Bindu Kalesan (2019). Changes in patterns of mortality rates and years of life lost due to firearms in the united states,1999 to 2016: A joinpoint analysisPLoS One, 14(11).
  18. Feng Li  & Zhuojing He (2019). Credit risk clustering in a business group: which matters more, systematic or idiosyncratic risk? Cogent Economics & Finance, page 1632528.
  19. Feng Li & Yanfei Kang* (2018). Improving forecasting performance using covariate-dependent copula models. International Journal of Forecasting, 34(3):456–476.
  20. Elizabeth C Pino, Yi Zuo, Camila Maciel DeOlivera, Shruthi Mahalingaiah, Olivia Keiser, Lynn L Moore, Feng Li, Ramachandran S Vasan, Barbara E Corkey  & Bindu Kalesan (2018). Cohort profile: The multistudy diabetes research (multitude) consortiumBMJ Open, 8(5):e020640.
  21. Yanfei Kang*, Rob J. Hyndman, Kate Smith-Miles. (2017). Visualising Forecasting Algorithm Performance using Time Series Instance SpaceInternational Journal of Forecasting 33(2): 345–358.
  22. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2015). Classes of Structures in the Stable Atmospheric Boundary LayerQuarterly Journal of the Royal Meteorological Society 141(691): 2057–2069. 
  23. Yanfei Kang. (2015). Detection, classification and analysis of events in turbulence time seriesBulletin of the Australian Mathematical Society 91(3): 521-522.
  24. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2014). Detecting and classifying events in noisy time seriesJournal of the Atmospheric Sciences 71(3): 1090–1104.
  25. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2014). A note on the relationship between turbulent coherent structures and phase correlationChaos: An Interdisciplinary Journal of Nonlinear Science 24(2) 023114: 1-6.
  26. Feng Li (2013). Bayesian Modeling of Conditional Densities. Ph.D. thesis, Department of Statistics, Stockholm University. ISBN: 978-91-7447-665-1.
  27. Feng Li  & Mattias Villani (2013). Efficient Bayesian multivariate surface regressionScandinavian Journal of Statistics, 40(4):706–723.
  28. Yanfei Kang, Danijel Belusic, Kate Smith-Miles. (2013). How to extract meaningful shapes from noisy time-series subsequences? In: Proceedings of the 2013 IEEE Symposium on Computational Intelligence and Data Mining (CIDM). IEEE, pp. 65–72.
  29. Yanfei Kang. (2012). Real-time change detection in time series based on growing feature quantization. In: Proceedings of the 2012 International Joint Conference on Neural Networks (IJCNN). IEEE, pp. 1–6.
  30. Feng Li, Mattias Villani  & Robert Kohn (2011.). Modeling conditional densities using finite smooth mixtures. In Kerrie Mengersen, Christian Robert, Mike Titterington (eds.), Mixtures: estimation and applications, pages 123–144. John Wiley & Sons Inc, Chichester.
  31. Feng Li, Mattias Villani  & Robert Kohn (2010). Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densitiesJournal of Statistical Planning and Inference,140(12):3638–3654


  1. Hyndman, R.J., & Athanasopoulos, G.著. 预测:方法与实践(第2版),康雁飞李丰(译)
  2. 李丰(2016)大数据分布式计算与案例。中国人民大学出版社。ISBN 9787300230276. [ 第二版在线预览 ]
  3. 康雁飞李丰(2021)统计计算。[ 在线预览版本 ]