A belated happy new year to everyone. Please see below for details of the first seminar of the year, and forward as appropriate. We also hope to put up a tentative schedule of the year's meetings within the next month on the Canberra branch website, so please stay tuned!

Date: Tuesday 26 February

5.15pm Refreshments, Allan Barton Forum, Level 2, Room 248, College of Business and Economics, ANU (Map).

6.00pm Presentation in Allan Barton Forum 

7.30pm After the talk, there will be a dinner at Briscola 60 Alinga St, Canberra (Restaurant).

Please RSVP SSA Canberra or reply to this email directly by 25 February if you would like to attend the dinner. 

Speaker: Peter Song, University of Michigan

Topic: Meta Estimation of Normal Mean Parameter:  Seven Perspectives of Data Integration and Beyond 

Abstract:

Data integration has recently drawn considerable attention in the statistical literature.  It is worth reviewing how pioneers of statistical science have thought of this important issue. This talk will present a synergistic treatment on the estimation of mean parameter of a normal distribution from seven different schools of statistics, which unveils critical insights on principles for the development of data integration analytics.  They include best linear unbiased estimation (BLUE), maximum likelihood estimation (MLE), Bayesian estimation, empirical Bayesian estimation (EBE), Fisher's fiducial estimation, generalized methods of moments (GMM) estimation, and empirical likelihood estimation (ELE).  Their properties of scalability and distributed inference will be discussed and compared analytically and numerically. 

Biography:

Dr. Song is Professor of Biostatistics and Associate Chair for Research at the Department of Biostatistics, School of Public Health in the University of Michigan, Ann Arbor.   He received his PhD in Statistics from the University of British Columbia, Vancouver, Canada in 1996.  He was a faculty member at the Department of Statistics and Actuarial Science, University of Waterloo, Canada (2004-2007) and a faculty member at the Department of Mathematics and Statistics, York University, Toronto, Canada (1996-2004). Dr. Song's research interests include big data analytics, high-dimensional data analysis, longitudinal data analysis, meta-analysis, missing data problems, spatiotemporal modeling, and statistical methods in omics data analysis. He is interested in data science applications in the areas of asthma, environmental health sciences, nephrology and nutritional sciences.  Dr. Song was awarded to prestigious John von Neumann’s Professorship at Technical University of Munich, Germany in 2013. He is ASA Fellow and Elected Member of International Statistical Institute. Dr. Song now serves as an Associate Editor of Journal of American Statistical Association, Canadian Journal of Statistics, and  Journal of Multivariate Analysis, and previously served as Associate Editor of Statistica Sinica, Journal of Statistical Planning and Inference, and Sankhya.  Dr. Song’s research is being currently funded by 9 active NIH and NSF grants.