Im Rahmen des Kolloquiums des Graduiertenkollegs Algorithmic Optimization findet am
Montag, dem 14. Mai 2018
16:00 Uhr c.t.
folgender Vortrag statt:
Big Data, Big Promise, Big Challenge: Can Small Area Estimation Play a Role in the Big Data Centric World?
P. Lahiri, Joint Program in Survey Methodology and Department of Mathematics, University of Maryland, College Park
The demand for various socioeconomic, transportation, and health statistics for small geographical areas is steadily increasing at a time when survey agencies are desperately looking for ways to reduce costs to meet fixed budgetary requirements. In the current survey environment, the application of standard sample survey methods for small areas, which require a large sample, is generally not feasible when considering the costs. One of the key factors that lead to the success of small area estimation (SAE) methodology is the availability of strong auxiliary variables. The accessibility of big data from different sources is now bringing new opportunities for statisticians to develop innovative SAE methods. In this talk, I will provide an outline of how SAE methods can be adapted to incorporate big data in improving local area statistics. Then I will discuss my recent collaboration with my UMD colleagues Professor Cinzia Cirillo of Department of Civil and Environmental Engineering, and Professor Joseph JaJa of Department of Electrical and Computer Engineering, and the University of Maryland Institute for Advanced Computer Studies (UMIACS). Finally, as an example from our different collaborative research projects, I will explain how SAE can help solve a seemingly different problem of predicting in real time traffic by exploiting rich vehicle probe big data.
Dr. Partha Lahiri is a Professor of Survey Methodology and Mathematics at the University of Maryland, College Park and an Adjunct Research Professor at the Institute of Social Research, University of Michigan, Ann Arbor. Before coming to Maryland, Dr. Lahiri was the Milton Mohr Distinguished Professor of Statistics at the University of Nebraska Lincoln. His research interests include big dat a, Bayesian statistics, record linkage, and small area estimation. Dr. Lahiri has served on a number of advisory committees, including the U.S. Census Advisory committee and U.S. National Academy panel. Over the years Dr. Lahiri advised various local and international organizations such as the United Nations Development Program, the World Bank, and the Gallup Organization. He is a Fellow of the American Statistical Association and the Institute of Mathematical Statistics and an elected member of the International Statistical Institute.