Index: Robert B. Gramacy
I am an Assistant Professor of Econometrics and Statistics in the Booth School of Business, and a fellow of the Computation Institute at The University of Chicago. My faculty webpage is here. You can find me in room HC338.
- My recent hockey paper was written up in Capital Ideas. We've started a blog to discuss new developments and weekly updates of our player ability metrics.
- My paper on variable selection and sensitivity analysis with dynamic trees featured as a science highlight at Argonne.
- A working paper on earnings forecasts was written up in Capital Ideas.
- A working paper on credit ratings was written up in Capital Ideas.
Teaching & Research Highlights
In the 2013-14 academic year I am teaching
- three sections of Applied Regression Analysis (BUS41100) in the Fall Quarter
- one section of Bayesian Inference (41913) in the Spring Quarter
My research interests include Bayesian modeling methodology, statistical computing, Monte Carlo inference, nonparametric regression, sequential design, and optimizaton under uncertainty. My application areas of interest include spatial data, sequential computer experiments, ecology, epidemiology, finance and public policy.
I am currently supervising the following students
- James Lawrence (2008/Statistical Laboratory): Sequential Monte Carlo methods for model selection in ecology
- Anne Sutkoff (2012/Chicago Booth): A regular vine copula approach to endogenous regressors in brand value estimation models
I participate in a cooperative statistical consulting effort with Scry Research.
Selected Recent Publications and Technical Reports
- Local Gaussian process approximation for large computer experiments (2013) with Dan Apley; preprint on arXiv:1303.0383
- Estimating player contribution in hockey with regularized logistic regression (2013) with Shane Jensen, and Matt Taddy. Journal of Quantitative Analysis in Sports, 9(1), pp. 97-111; preprint on arXiv:1209.5026; also see our Capital Ideas article and blog.
- Variable selection and sensitivity analysis via dynamic trees with an application to computer code performance tuning (2013) with Matt Taddy and Stefan Wild. Annals of Applied Statistics, 7(1), pp. 51-80; preprint on arXiv:1108.4739; also see our science highlight at Argonne
- Dynamic trees for streaming and massive data contexts (2012) with Christoforos Anagnostopoulos; preprint on arXiv:1201.5568
- Cases for the nugget in modeling computer experiments (2012) with Herbie Lee. Statistics and Computing, 22(3), pp. 713-722; preprint on arXiv:1007.4580
Robert B. Gramacy -- 2013