Modern sufficient dimension reduction methods for complex dependent data. This project aims to develop a suite of modern statistical theory and methods for sufficient dimension reduction in data exhib

Description

Modern sufficient dimension reduction methods for complex dependent data. This project aims to develop a suite of modern statistical theory and methods for sufficient dimension reduction in data exhibiting complex dependence structures. In doing so, it will address a pressing need for statistical tools that can accurately distil high-dimensional regression and classification relationships, with little to no loss of information, into results readily understood by domain experts. The project is expected to unlock valuable insights into how various spatial, temporal, and sampling processes operate together to drive dynamics in bioinformatics and social network data. This will provide important long-term benefits to enhance biological discovery and combat the spread of misinformation in online digital environments.. Scheme: Discovery Projects. Field: 4905 - Statistics. Lead: Dr Hoang Linh Nghiem