
Andrew Gelman
Department of Statistics and Department of Political Science, Columbia University, USA
Monday 18 January 2010
16.00
Seminar Room B10 (Basement)
Alexandra House, 17 Queen Square, London, WC1N 3AR
Creating structured and flexible models: some open problems
A challenge in statistics is to construct models that are structured enough to be able to learn from data but not be so strong as to overwhelm the data. We introduce the concept of "weakly informative priors" which contain important information but less than may be available for the given problem at hand. We also discuss some related problems in developing general models for taxonomies and deep interactions. We consider how these ideas apply to problems in social science and public health. If you don't walk out of this talk a Bayesian, I'll eat my hat.
Link for the talk:
http://www.stat.columbia.edu/~gelman/research/presentations/mittalk2.pdf
Link to a paper:
http://www.stat.columbia.edu/~gelman/research/published/priors11.pdf