Research Interests
My main area of research interest is the development of Bayesian methodology for the analysis of modern, complex datasets. I am particularly interested in the development of computational methods to address these problems, with recent focus on the use of parallel computing in statistics.
Specific methodological research areas include the problems of variable selection and model uncertainty in contexts of regression, prediction and complex multivariate modeling with many variables. A key element of this research is the development of stochastic search and MCMC methods for exploring large model spaces.
Links to Research Activities
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A recent version of the RMSSS talk...
Regression Model Shotgun Stochastic Search -
Second Workshop on Monte Carlo Methods
Harvard University - August 2005 (with Mike West)
Stochastic Search and Sparsity in High-Dimensional Regression and Graphical Models -
Joint Statistical Meetings
Toronto, Canada - August 2004
Bayesian Inferences on Umbrella Orderings