This research has as its basic theme the development of likelihood and likelihood-based methods for statistical models in which conventional likelihood methods are poorly understood or are known to fail. The topics fall into several main categories. These are semiparametric density estimation, mixture estimation and testing, composite likelhood, nuisance parameters, and algorithms. This reseach in the general area of statistics. It aims to extend the scope of scientific problems that can rigorously analyzed.
