Advanced Mixture Models for the Analysis of Modern-Day Data (2014–2017)

Extracting key information from huge data sets is critical to the scientific successes of the future. We will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation, we develop mixtures of factor models with options for skew distributions that can be used to effectively analyse such data. Key applications include the domains of bioinformatics, biostatistics, business, data mining, economics, finance, image analysis, marketing, and personalized medicine, among many others.
Grant type:
ARC Discovery Projects
Funded by:
Australian Research Council