11月16日 | 杨宇红:Forecast Combination Puzzle: What Is Really Going on?

时间:2022-11-14浏览:24设置


时   间:2022年11月16日(周三) 9:00-10:30

地   点:线上,腾讯会议:738-3897-6027  线下:理科大楼A1716

题   目:Forecast Combination Puzzle: What Is Really Going on?

报告人:杨宇红 教授 明尼苏达大学

主持人:方方 教授

主   办:统计学院

摘   要:

It is often reported in the forecast combination literature that a simple average of candidate forecasts is more robust than sophisticated combining methods. This phenomenon is usually referred to as the “forecast combination puzzle”. What is really going on here? We will examine the puzzle from multiple perspectives, including combination versus selection, different goals of forecast combination. Based on our new understandings, both simulations and real data evaluations are conducted to illustrate the causes of the puzzle. We further propose a multi-level AFTER strategy that can integrate the strengths of different combining methods and adapt intelligently to the underlying scenario. In particular, by treating the simple average as a candidate forecast, the proposed strategy is shown to reduce the heavy cost of estimation error and, to a large extent, mitigate the puzzle.

报告人简介:

杨宇泓,1988年获中国科大数学学士,1993年获伊利诺伊大学统计硕士,1996年获得耶鲁大学统计学博士,即加入Iowa State University统计学任助理教授,2001年升为副教授。从2007年起为明尼苏达大学School of Statistics教授。他在统计、机器学习、高维数据等方向建立了深入的理论和方法,2010年成为数理统计学会会士。他担任或曾担任数家重要统计杂志副编(ASSOCIATE EDITOR),包括Annals of Statistics, Statistica Sinica, Annals of Institute of Statistical Mathematics, Statistical Survey, JSPI。其研究兴趣包括高维数据分析理论,模型选择和组合,多臂老虎机问题(Multi-Arm Bandit),精准医学统计问题,预测等。他曾主持4项国家科研项目,包括NSF CAREER Award。其研究成果包括80余篇学术论文,其中18篇为单作者(single author)。这些论文发表在统计、机器学习、信息论、计量经济、预测、逼近论等领域顶尖刊物,包括Annals of Statistics, JASA, Biometrika, JRSSB, IEEE Transactions on Information Theory, Journal of Econometrics, Journal of Approximation Theory, Journal of Machine Learning Research, and International Journal of Forecasting。他的研究成果在多个领域的应用有广泛的影响,Google Scholar 上有近六千次引用 。杨教授已经给出约150个学术会议邀请报告和应邀学术讲座。他为学术杂志审稿超过300篇,也为美国、加拿大、以色列、荷兰、比利时、香港等国家或地区评审研究基金或终身教授数十项。


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