Project level: PhD, Masters, Honours

Finite mixture distributions have become increasingly popular in the modelling and analysis of data due to their flexibility. This use of finite mixture distributions to model heterogeneous data has undergone intensive development in the past decades, as witnessed by the numerous applications in various scientific fields such as bioinformatics, genetics, information processing, medicine, and pattern recognition, among many others. In this project, the intent is to investigate some of the issues associated with the fitting of mixture models via maximum likelihood.

Project members

Professor Geoffrey McLachlan