Jon A. Wellner will carry out research on empirical processes, bootstrap methods in statistics, semiparametric models, and inverse problems and nonstandard asymptotics. The research will involve limit theory for infinite - dimensional M - estimates and related bootstrap methods, preservation theorems for uniform Donsker classes of functions, uniform in $~P~$ bootstrap limit theorems, estimation of monotone and convex functions, convergence of iterative convex minorant algorithms, and the behavior of global functionals in models with interval censoring. Applications include bivariate models with covariates, regression models under interval censoring, and studies of nonparametric maximum likelihood estimators. Jon A. Wellner will carry out research in statistics. The research will involve large sample limit theory for new estimators in problems with large (infinite - dimensional) parameter spaces.
