物流研究中心沙龙 (5月18日下午)

发布时间:2018-05-17浏览次数:2

报告题目:Robust Estimation for analysing time Series Data

报告人:Professor You-Gan Wang, Queensland University of Technology (QUT)

Professor Wang is currently Professor of Applied Statistics in Data Science at Queensland University of Technology (QUT), Australia. His work has substantial impacts and scientific innovations in natural resource modelling and management. His research innovation is coupled by successful applications of the developed methodology in hydrology, marine and biological sciences (150+ publications). He also has extensive experience in student supervision. Professor Wang has international work experiences. He obtained his PhD from Oxford University, and had senior positions at Harvard University, National University of Singapore and CSIRO Australia.

时间:5月18日周五下午12:30-13:30

地点:泰山科研楼409

摘要:One challenging task in analyzing time series data is how to achieve robustness in presence of outliers while maintaining high estimation efficiency so that we can draw valid conclusions and provide useful advices. We propose a data driven method which leads to more efficient parameter estimation. This data-dependent approach allows us to choose a regularization (tuning) parameter that depends on the proportion of `outliers' in the data so that estimation efficiency is maximized. We illustrate the proposed methods using a study on ammonium nitrogen concentrations from two sites in the Huaihe River in China, where the interest is in quantifying the trend in the most recent years while accounting for possible temporal correlations and `irregular' observations in earlier years.



报告题目:Challenges in the Belt and Road Research Agenda

报告人:Professor Paul Tae-Woo Lee,Zhejiang University

Director, Institute of Maritime Logistics

Ocean College, Zhejiang University

Associate Editor,Transportation Research Part E

时间: 5月18日周五下午13:30-14:30

地点: 泰山科研楼409

摘要:Professor Lee will share his observations in reviewing more than 100 papers related to B&R and how to solve challenges researchers are facing now.


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