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Feng Li
Associate Professor, Guanghua School of Management, Peking University
Подтвержден адрес электронной почты в домене gsm.pku.edu.cn - Главная страница
Название
Процитировано
Процитировано
Год
Forecasting: theory and practice
F Petropoulos, D Apiletti, V Assimakopoulos, MZ Babai, DK Barrow, ...
International Journal of Forecasting 38 (3), 705-871, 2022
7292022
GRATIS: GeneRAting TIme Series with diverse and controllable characteristics
Y Kang, RJ Hyndman, F Li
Statistical Analysis and Data Mining: The ASA Data Science Journal 13 (4 …, 2020
145*2020
Forecast combinations: An over 50-year review
X Wang, RJ Hyndman, F Li, Y Kang
International Journal of Forecasting 39 (4), 1518-1547, 2023
1412023
Forecasting with time series imaging
X Li, Y Kang, F Li
Expert Systems with Applications 160, 113680, 2020
922020
Least-square approximation for a distributed system
X Zhu, F Li, H Wang
Journal of Computational and Graphical Statistics 30 (4), 1004-1018, 2021
482021
Distributed ARIMA models for ultra-long time series
X Wang, Y Kang, RJ Hyndman, F Li
International Journal of Forecasting 39 (3), 1163-1184, 2023
462023
Flexible modeling of conditional distributions using smooth mixtures of asymmetric student t densities
F Li, M Villani, R Kohn
Journal of Statistical Planning and Inference 140 (12), 3638-3654, 2010
442010
Forecast with forecasts: Diversity matters
Y Kang, W Cao, F Petropoulos, F Li
European Journal of Operational Research 301 (1), 180-190, 2022
322022
FFORMPP: Feature-based forecast model performance prediction
TS Talagala, F Li, Y Kang
International Journal of Forecasting 38 (3), 920-943, 2022
302022
Déjà vu: A data-centric forecasting approach through time series cross-similarity
Y Kang, E Spiliotis, F Petropoulos, N Athiniotis, F Li, V Assimakopoulos
Journal of Business Research 132, 719-731, 2021
252021
Improving forecasting performance using covariate-dependent copula models
F Li, Y Kang
International Journal of Forecasting 34 (3), 456-476, 2018
24*2018
Hierarchical forecasting with a top-down alignment of independent-level forecasts
M Anderer, F Li
International Journal of Forecasting 38 (4), 1405-1414, 2022
22*2022
The uncertainty estimation of feature-based forecast combinations
X Wang, Y Kang, F Petropoulos, F Li
Journal of the Operational Research Society 73 (5), 979-993, 2022
182022
A note on distributed quantile regression by pilot sampling and one-step updating
R Pan, T Ren, B Guo, F Li, G Li, H Wang
Journal of Business & Economic Statistics 40 (4), 1691-1700, 2022
152022
Changes in patterns of mortality rates and years of life lost due to firearms in the United States, 1999 to 2016: A joinpoint analysis
HM Bailey, Y Zuo, F Li, J Min, K Vaddiparti, M Prosperi, J Fagan, S Galea, ...
PLoS One 14 (11), e0225223, 2019
142019
Bayesian forecast combination using time-varying features
L Li, Y Kang, F Li
International Journal of Forecasting 39 (3), 1287-1302, 2023
122023
Intersections of firearm suicide, drug-related mortality, and economic dependency in rural America
B Kalesan, S Zhao, M Poulson, M Neufeld, T Dechert, JJ Siracuse, Y Zuo, ...
Journal of surgical research 256, 96-102, 2020
122020
Feature-based intermittent demand forecast combinations: accuracy and inventory implications
L Li, Y Kang, F Petropoulos, F Li
International Journal of Production Research 61 (22), 7557-7572, 2023
112023
Modelling conditional densities using finite smooth mixtures
F Li, M Villani, R Kohn
Mixtures: estimation and applications, 123-144, 2011
102011
Efficient Bayesian multivariate surface regression
F Li, M Villani
Scandinavian Journal of Statistics 40 (4), 706-723, 2013
92013
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Статьи 1–20