Bayesian copula modelling of multivariate dependence: getting to grips with data that is far from normal. Copula models are very popular tools that are changing the way analysts deal with information rich data in fields as diverse as marketing, finance and transport studies. This project aims to improve and extend these tools, so that more accurate and reliable models can be employed, resulting in improved evidence-based decision-making.
Flexible Models and Methods for Longitudinal Data. The availability of increasingly large data sets offers the potential to improve understandings of many phenomena. However, without models for these phenomenon and methods to analyse the data generated by them, information contained in such data cannot be extracted. This project aims to advance statistical methods and models for analysing data that are collected on a large number of individuals at many time points. In particular, data collected ....Flexible Models and Methods for Longitudinal Data. The availability of increasingly large data sets offers the potential to improve understandings of many phenomena. However, without models for these phenomenon and methods to analyse the data generated by them, information contained in such data cannot be extracted. This project aims to advance statistical methods and models for analysing data that are collected on a large number of individuals at many time points. In particular, data collected from mobile phone applications will be used to understand the effect that training regimes have on cognitive functioning and how these effects vary with individual characteristics.Read moreRead less
Bayesian analysis of individual decisions in health and labour economics. This project aims to exploit emerging Bayesian Markov chain Monte Carlo methods to develop new approaches to modelling economic decision making. These methods will generate insights into two current and important policy debates. This includes (i) marijuana, alcohol and tobacco use and legalisation of marijuana use; and (ii) parental leave policies, maternity leave decisions and mothers' labour market dynamics. Although p ....Bayesian analysis of individual decisions in health and labour economics. This project aims to exploit emerging Bayesian Markov chain Monte Carlo methods to develop new approaches to modelling economic decision making. These methods will generate insights into two current and important policy debates. This includes (i) marijuana, alcohol and tobacco use and legalisation of marijuana use; and (ii) parental leave policies, maternity leave decisions and mothers' labour market dynamics. Although policies play an important role in observed health and labour market behaviours, their exact effects on individuals' decisions and outcomes are often difficult to quantify due to the complex nature of the decision process. Outcomes from the project will include new evidence of changes in substance uses under different legal scenarios and provide benefits such as yielding vital evidence on labour market and health behaviour impacts to support policy makers and strengthen Australia's research capacity in Bayesian analysis.Read moreRead less
A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it ....A Bayesian State Space Methodology for Forecasting Stock Market Volatility and Associated Time-varying Risk Premia. Accurate prediction of stock market volatility is critical for effective financial risk management. Along with information on volatility embedded in historical stock market returns, the prices of options written on the underlying stocks also reflect the option market's assessment of future volatility. This project will exploit this dual data source in a completely new way, using it to produce forecasts of both volatility itself and the premia factored into asset prices as a result of traders' perceptions of volatility risk. State-of-the-art statistical methods will be used to produce up-dates of the probability of extreme volatility and/or extreme risk aversion, as new market data becomes available each trading day.Read moreRead less
Maximizing solid state Nuclear Magnetic Resonance (NMR) with maximum entropy. Nuclear magnetic resonance is an essential technology for the characterisation of important industrial and biomedical molecules, molecular chains and complexes. This project aims to considerably expand the fundamental capability of experimental techniques for the study of materials in the solid state, in particular for a new class of biological nanoparticle. These advances will have important global implications for re ....Maximizing solid state Nuclear Magnetic Resonance (NMR) with maximum entropy. Nuclear magnetic resonance is an essential technology for the characterisation of important industrial and biomedical molecules, molecular chains and complexes. This project aims to considerably expand the fundamental capability of experimental techniques for the study of materials in the solid state, in particular for a new class of biological nanoparticle. These advances will have important global implications for research into life-saving therapeutic strategies aimed at many pharmaceutical targets embedded in cell membranes, protein misfolding disorders such as Alzheimer's disease and Huntington's disease, as well as development of the next generation of "green" plastics and other advanced polymers.Read moreRead less
New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutriti ....New nonparametric statistical methods for imperfectly observed data. Statistical science today is facing the challenge of having to answer questions about data that are more complex than ever before. Some of the major difficulties are caused by the lack of direct access to quantities of interest, and the more intricate structure of the available data. Motivated by applications in areas such as cancer and genetic studies, infectious disease, environmental pollution, and public health and nutrition, this project aims to develop novel and highly effective statistical methodology for solving contemporary problems involving new types of imperfectly observed data. The expected outcomes will solve frontier problems, where information can only be accessed through sophisticated computer intensive methods.Read moreRead less
Advanced magnetic resonance imaging methods for the characterisation of brain structure and function. Magnetic resonance imaging (MRI) is a non-invasive method that has revolutionised the development of neuroscience and neurology. The goal of this project is to develop advanced MRI methods for the study of brain structure and function which will be applied to the investigation of epilepsy and stroke.
Design, analysis and application of Monte Carlo methods in statistical mechanics. Statistical mechanics is a general framework for studying complex systems and Monte Carlo methods are an important computational tool in such studies. This project will develop new, vastly more efficient, Monte Carlo methods for problems in statistical mechanics, and will apply these methods to real-world problems such as urban traffic flow.
Statistical Modelling in the Era of Data Science: Theory and Practice. This project aims to develop innovative statistical methodology that is interpretable, theoretically justified, and scalable to today's growing complex data. With the influx of data being collected in both the public and private sectors, making sense of this data is a fundamental task. Through a rigorous modelling framework, this project intends to facilitate the discovery of knowledge by developing powerful new tools to extr ....Statistical Modelling in the Era of Data Science: Theory and Practice. This project aims to develop innovative statistical methodology that is interpretable, theoretically justified, and scalable to today's growing complex data. With the influx of data being collected in both the public and private sectors, making sense of this data is a fundamental task. Through a rigorous modelling framework, this project intends to facilitate the discovery of knowledge by developing powerful new tools to extract insight from these complex datasets. The outcomes of this project will benefit society by providing techniques to enable research advances and inform decision-making for a broad base of disciplines, including applications to network security, energy forecasting, environmental monitoring, and public health. Read moreRead less
Computational studies of soft matter. Soft matter systems such as colloidal suspensions and polymers are ubiquitous in nature, and industrially important. For colloidal systems, specifically hard spheres, this project will utilise new algorithms to attack long standing questions about the nature of the virial series. For self-avoiding walks and related models of polymers, research studies have recently developed radically improved Monte Carlo simulation algorithms. These algorithms will enable t ....Computational studies of soft matter. Soft matter systems such as colloidal suspensions and polymers are ubiquitous in nature, and industrially important. For colloidal systems, specifically hard spheres, this project will utilise new algorithms to attack long standing questions about the nature of the virial series. For self-avoiding walks and related models of polymers, research studies have recently developed radically improved Monte Carlo simulation algorithms. These algorithms will enable this project to simulate polymers which may be as long as DNA, and to calculate physical properties with unprecedented precision. The software developed for studying polymers will be released as an open source software library which will revolutionise the field of polymer simulation.Read moreRead less