Table of Contents
- Research Profile is available at Microsoft Academic & Google Scholar.
- Citation network for all publications is available at Microsoft Academic.
- Xuening Zhu, Feng Li*, & Hansheng Wang (2021). Least squares approximation for a distributed system. Journal of Computational and Graphical Statistics. (in press).
- 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).
- Yanfei Kang, Evangelos Spiliotis, Fotios Petropoulos, Nikolaos Athiniotis, Feng Li*, & Vassilios Assimakopoulo (2021). Déjà vu: A data-centric forecasting approach through time series cross-similarity, Journal of Business Research. (in press).
- Xixi Li, Yanfei Kang, & Feng Li* (2020). Forecasting with time series imaging, Expert Systems with Applications 160: 113680.
- Yanfei Kang, Rob J Hyndman, & Feng Li* (2020). GRATIS: GeneRAting TIme Series with diverse and controllable characteristics, Statistical Analysis and Data Mining 13(4): 354-376.
- Chengcheng Hao, Feng Li, & Dietrich von Rosen (2020). A Bilinear Reduced Rank Model, In Jianqing Fan and Jianxin Pan (eds.), Contemporary Experimental Design, Multivariate Analysis and Data Mining, Springer.
- Hyndman, R.J., & Athanasopoulos, G.著. 预测：方法与实践（第2版），康雁飞、李丰（译）https://otexts.com/fppcn/
- 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 analysis. PLoS One, 14(11).
- Feng Li & Zhuojing He (2019). Credit risk clustering in a business group: which matters more, systematic or idiosyncratic risk? Cogent Economics & Finance, page 1632528.
- Feng Li & Yanfei Kang (2018). Improving forecasting performance using covariate-dependent copula models. International Journal of Forecasting, 34(3):456–476.
- 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) consortium. BMJ Open, 8(5):e020640.
- 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.
- [ Online version ]
- Feng Li (2013). Bayesian Modeling of Conditional Densities. Ph.D. thesis, Department of Statistics, Stockholm University. ISBN: 978-91-7447-665-1.
- Feng Li & Mattias Villani (2013). Efficient Bayesian multivariate surface regression. Scandinavian Journal of Statistics, 40(4):706–723.
- 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.
- Feng Li, Mattias Villani & Robert Kohn (2010). Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densities. Journal of Statistical Planning and Inference,140(12):3638–3654
- Development of the Methodologies of Objective Performance Criteria Based Single-Armed Trials for The Clinical Evaluation of Traditional Chinese Medicine. funded by National Natural Science Foundation of China, (2020-). Major Investigator.
- Efficient Bayesian Flexible Density Methods with High Dimensional Financial Data funded by National Natural Science Foundation of China, (2016-2019). Principal investigator.
- Bayesian Multivariate Density Estimation Methods for Complex Data funded by Ministry of Education, China (2014-2016). Principal investigator
PDF slides are available for download.
- ICSA Conference on Data Science, January 11-13, 2019, Xishuangbanna, China.
- School of Data Science, Fudan University, Oct 28-30, 2017, Shanghai, China
- IMS-China International Conference on Statistics and Probability, June 28 – July 1, 2017, Nanning, China.
- The 1st International Conference on Econometrics and Statistics, Hong Kong, 15-17 June 2017.
- The 2016 World Meeting of the International Society for Bayesian Analysis, Jun 13—17, 2016, Sardinia, Italy.
- IMS-China International Conference on Statistics and Probability, June 1-4, 2015, Kunming, China.
- International Symposium on Financial Engineering and Risk Management 2014, June 27, 2014, Beijing, China.
- Guanghua School of Management, Peking University, Oct 14, 2013, Beijing, China
- The Stockholm University Forskardagarna, 2-3 Oct, 2013, Stockholm, Sweden.
- The 59th World Statistics Congress, August 25-29, 2013, Hong Kong.
- The 2012 World Meeting of the International Society for Bayesian Analysis, Jun 25—29, 2012, Japan.
- The third Linnaeus University Workshop in Stochastic Analysis and Applications, May 24—25, 2012, Växjö, Sweden.
- Workshop on “Analysis of High-Dimensional Data”, Jönköping International Business School, Feb 16—17, 2012, Sweden.
- The LiU Seminar Series in Statistics and Mathematical Statistics, Linköping University, Oct 11, 2011, Sweden.
- The 42nd Winter Conference in Statistics — Incomplete data: semi-parametric and Bayesian methods, Mar 6—10, 2011, Sweden.
- The 2010 World Meeting of the International Society for Bayesian Analysis, Jun 3—8, 2010, Spain.
Recent academic visits
- 2014 Aug, Toronto University, Canada
- 2013 Oct, Stockholm University, Sweden
- 2011 Sep – 2012 March, Linköping University, Sweden
- 2011 June, University of Southampton, UK
- 2009 May, Erasmus University Rotterdam, The Netherlands