Improved theory and practice in econometric modelling of nonlinear spatial time series. Modern Australia faces many challenges in economic and global climate changes, which require advanced statistical technologies in modeling and forecasting of econometric spatial time series data. This project will provide flexible models and methods that enable practitioners to more accurately measure and manage economic and climatic risks.
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
Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network sec ....Frontiers in Data Science: Analysing Distributions as Data. This project aims to develop the statistical foundations of a new approach to analysing large and complex data, based on building distributional approximations of the data, which can then be analysed by standard statistical methods. The need to analyse very large and complex datasets has become a vital part of everyday life, particularly in the analysis of national problems in public health, environmental pollution, computer network security and climate extremes. The project expects to change our way of thinking in how to be smarter about what data we use (and collect) for analysis, rather than relying on brute force analysis of large datasets. The project is expected to transform the knowledge base of the discipline, and the resulting techniques will enable across-the-board research advances for many industries and disciplines.Read moreRead less
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
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
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.
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
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.
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
Oceanic gateways: a primary control on global climate change? The opening and closing of oceanic gateways, narrow passageways facilitating exchange between ocean basins, has been linked to major changes in Earth’s climate. This project will link the disparate fields of geodynamics and palaeo-climatology, for the first time, through an innovative methodology that models the changing width and depth of ocean gateways through time. It will address the role of gateways in modulating Earth’s climate ....Oceanic gateways: a primary control on global climate change? The opening and closing of oceanic gateways, narrow passageways facilitating exchange between ocean basins, has been linked to major changes in Earth’s climate. This project will link the disparate fields of geodynamics and palaeo-climatology, for the first time, through an innovative methodology that models the changing width and depth of ocean gateways through time. It will address the role of gateways in modulating Earth’s climate at key periods during the planet’s transition from a “Greenhouse” to “Icehouse” World.Read moreRead less