Organized by
Department of Mathematics

Optimization Techniques to Deal with Lack of Data
in Statistical Estimation

Professor Roger J-B Wets

Distinguished Research Professor of Mathematics, University of California, Davis
G.B. Dantzig Prize in Mathematical Programming, 1994
Lanchester Prize (INFORMS), 1998
Guggenheim Fellowship, 1982-83
Erskine Fellowship, 1991


Date: 14 February 2011 (Monday)

11:00am - 12:00noon (Preceded by Reception at 10:30am)


FSC1217, Fong Shu Chuen Building,
Ho Sin Hang Campus, Hong Kong Baptist University



To describe the stochastic environment in descriptive or prescriptive models, it is implicitly assumed that enough data will be available to guarantee the validity of a decision or the consistency of a statistical estimate. Unfortunately, in a real life environment the data available is rarely enough to reach the asymptotic range, either because it is not available or there is not enough time to collect an adequate data base before decisions or estimates must be produced. One serious shortcoming is our ability to systematically blend data and non-data information, in other words, our inability to deal with the fusion of hard and soft information. The lecture deals with these challenges.




All are welcome