Applied robust Bayesian analysis
Applied robust Bayesian analysis adds the dimension of probabilistic imprecision to standard model-based uncertainty analyses. The robust Bayesian approach employs sets of probability measures to describe uncertainty, rather than precise values. This concept has the potential to capture ambiguity or disagreement in probability specification in a variety of ways and therefore can provide a more realistic portrayal of scientific knowledge. The objective of our research in this area is to bring the strengths of the robust Bayesian approach to bear on the problem of separating sources of uncertainty in environmental model-based assessments.
Faculty contact: Mark E. Borsuk