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
Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and ....Improving productivity: theory and application to Australian hospitals. This project aims to improve existing methods for analysing productivity and efficiency of organisations. The new methods will be applied to Australian hospitals, to analyse their productivity and efficiency, identify the best-practices and their determinants and recommend improvements and necessary reforms. The high level of healthcare costs in Australia, about 5 percent of gross domestic product, as well as their rapid and accelerating growth, imply that application of methods developed through this project may save billions of dollars and, more importantly, thousands of lives. An expected outcome of this project will be superior theoretical and practical methods for analysing productivity and efficiency of economic systems, to enhance understanding of the potential for improvements and of the necessary reforms.Read moreRead less
Solving and estimating dynamic models of strategic interaction. This project aims to investigate how firms interact with each other through time and how these interactions drive both the operation of, and value created in, economic markets. While recent theoretical models predominantly capture the complexity of these dynamic interactions, the methods for testing these models’ predictions against observed data do not. Instead, they are based on a range of simplifying assumptions that undermine th ....Solving and estimating dynamic models of strategic interaction. This project aims to investigate how firms interact with each other through time and how these interactions drive both the operation of, and value created in, economic markets. While recent theoretical models predominantly capture the complexity of these dynamic interactions, the methods for testing these models’ predictions against observed data do not. Instead, they are based on a range of simplifying assumptions that undermine the reliability of their analysis. This project will develop statistical and computational methods to better understand observed economic behaviour. By allowing the effects of proposed economic interventions and regulations ex ante, this project will support the development of more efficient and better-targeted policies in every area of the economy.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
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.
Scalable and Robust Bayesian Inference for Implicit Statistical Models. This project aims to develop the next generation of efficient methods for fitting complex simulation-based statistical models to data. Practitioners and scientists are interested in such implicit models to enable discoveries, produce accurate predictions and inform decisions under uncertainty. However, the associated computational cost has restricted researchers to implicit models that must have a small number of parameters ....Scalable and Robust Bayesian Inference for Implicit Statistical Models. This project aims to develop the next generation of efficient methods for fitting complex simulation-based statistical models to data. Practitioners and scientists are interested in such implicit models to enable discoveries, produce accurate predictions and inform decisions under uncertainty. However, the associated computational cost has restricted researchers to implicit models that must have a small number of parameters and be well specified, impeding scientific progress. This project will develop new computational methods and algorithms for implicit models that scale to high dimensions and are robust to misspecification. Benefits will arise from the more routine use of implicit models in epidemiology, biology, ecology and other fields.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
Integrated Nanoplatform for Multiomics Analysis of Cell-to-Cell Interaction. This project aims to develop an integrated nanoplatform for analysis of exosomes produced by host-pathogen interaction at the single cell level. This will be accomplished by engineering an innovative device involving plasmonic nanoparticles to probe exosomes molecular profiles over time. The intended outcome is a generic and robust platform for detailed molecular analysis of the consequences of cell-to-cell interactions ....Integrated Nanoplatform for Multiomics Analysis of Cell-to-Cell Interaction. This project aims to develop an integrated nanoplatform for analysis of exosomes produced by host-pathogen interaction at the single cell level. This will be accomplished by engineering an innovative device involving plasmonic nanoparticles to probe exosomes molecular profiles over time. The intended outcome is a generic and robust platform for detailed molecular analysis of the consequences of cell-to-cell interactions. Single cell scale will greatly improve detection accuracy for heterogeneous cell populations. Benefits will include new knowledge of cell-to-cell communication and intellectual property in manufacturing, which will foster collaborations across institutions and Australian industry by providing new technological solutions.Read moreRead less