Fifth Announcement of ROSE Seminar, Institute of Statistics and Applied Mathematics, Anhui University of Finance and Economics
Date: 2018-06-14 Views: 27

Fifth Announcement of ROSE Seminar, Institute of Statistics and Applied Mathematics, Anhui University of Finance and Economics

ROSE Seminar (Research on Statistics & Econometrics seminar) of Anhui University of Finance and Economics was initiated by the Institute of Statistics and Applied Mathematics of Anhui University of Finance and Economics. The forum adheres to communicate and improve the academic style. The high-level academic papers with meaningful topics, innovative methods, and rigorous arguments are aimed at improving the professional level of academic exchange platform for both internal and domestic statistical and econometricians.

The fifth period of the ROSE Seminar will be held on June 15, 2018. ROSE Seminar is an open academic exchange forum that not only provides opportunities for our school’s teachers and students to communicate, but also provides opportunities for teachers and students at home and abroad. This time we are very honored to invite Prof. Delin Chu from the National University of Singapore to write a report entitled Regularized incremental linear discriminant on large-scale data, Professor Lei Hua from Northern Illinois University and Professor Michelle Xia respectively will have reports entitled Full-range tail Dependence copulas and applications,Statistical models adjusting for misrepresentation in heavy-tailed loss models report. Teachers and students on and off campus are welcome to participate in exchange discussions.

  

  

  

  

Report time,site

Content of report

Time2:40pm, June 15,2018

SiteEconomic and Statistical   Analysis Department of the 3rd Floor, Administrative Building, No. 2, West   Campus, Anhui University of Finance and Economics

TitleRegularized incremental   linear discriminant on large-scale data

ReporterDelin Chu

TitleFull-range tail dependence   copulas and applications

ReporterLei Hua

TitleStatistical models adjusting   for misrepresentation in heavy-tailed loss models

ReporterMichelle Xia