Martin Wells' research
interests center on applied and theoretical statistics and sometimes cross
the boundary into applied probability.
He has worked on inference questions in
credit risk, economic damages, epidemiology, finance (physical and risk
neutral worlds), graphical models, legal studies, microarrays,
proteomics, quantitative trait loci, extremes, data networks and has
considered estimation problems for heavy-tailed phenomena. His theoretical
research has focused on Bayesian statistics, biostatistics, conditional
inference, evidence assessment, functional data, hypothesis testing,
saddlepoint approximations, and shrinkage estimation.