Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of ....Classification of Microarray Gene-Expression Data. The broad aim is to provide statistical methodology for the classification of microarray gene-expression data. Microarrays are part of a new biotechnology that allows the monitoring of expression levels for thousands of genes simultaneously. The explosion in microarrays has produced massive quantities of data that require new statistical techniques for analysis in order to exploit their enormous scientific potential. One of the main uses of the methodology to be developed is to expedite the discovery of new subclasses of diseases. Another is to provide prediction rules for the diagnosis and treatment of diseases.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research w ....Entropic Analysis of Financial Risk and Uncertainty. The recent financial crisis has shown that the financial markets are not as stable as expected, and are at risk from a lack of knowledge about new financial products and their risks. This research provides a framework to better measure and forecast financial risks by applying a set of techniques known collectively as entropic analysis as a novel way to measure the amount of information that can be extracted from historical data. The research will facilitate the design of policies and regulations by regulatory authorities that need to evaluate new financial products, their associated risks and their impacts on the financial markets.Read moreRead less
Bayesian Inference for Flexible Parametric Multivariate Econometric Modelling. The anticipated outcomes include the development of enhanced multivariate econometric models and innovative computationally intensive methods for their estimation. These models are used in numerous and diverse applications which are data-intensive and where more complete models will greatly enhance data-based decision-making. Results include improved information use in the wholesale electricity markets, in financial m ....Bayesian Inference for Flexible Parametric Multivariate Econometric Modelling. The anticipated outcomes include the development of enhanced multivariate econometric models and innovative computationally intensive methods for their estimation. These models are used in numerous and diverse applications which are data-intensive and where more complete models will greatly enhance data-based decision-making. Results include improved information use in the wholesale electricity markets, in financial market investment decision-making and for the assessment of the impact of internet advertising.Read moreRead less
Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology wi ....Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology will be applied to the analysis of medical imaging data and to the estimation of spatial econometric models of residential real estate prices. The expected outcomes include developments in the frontier framework of Bayesian computational estimation methodology, improved methods for medical image processing and estimation of high resolution spatial models of residential real estate prices in Australian metropolitan centres.Read moreRead less
Assessing and enhancing the quality of longitudinal survey data. Australia has begun investing heavily in the collection of population-wide longitudinal survey data. Most of that effort has focused first on collection and dissemination and second on analysis, with scant attention paid to the quality of data collected. This is unfortunate given that longitudinal surveys exhibit many problems (e.g., attrition, panel conditioning, and seam effects) that are not relevant in more ubiquitous cross-sec ....Assessing and enhancing the quality of longitudinal survey data. Australia has begun investing heavily in the collection of population-wide longitudinal survey data. Most of that effort has focused first on collection and dissemination and second on analysis, with scant attention paid to the quality of data collected. This is unfortunate given that longitudinal surveys exhibit many problems (e.g., attrition, panel conditioning, and seam effects) that are not relevant in more ubiquitous cross-section of surveys. Without adequate resources devoted to these methodological issues, the quality of substantive research will be questioned and interest from potential users decline. Maximizing the investment being made in longitudinal data thus requires a complementary investment in methodological research.Read moreRead less
The role of households, neighbourhoods and networks in social statistics. Many issues affect the social progress of the country. Social research can determine the factors affecting issues such as unemployment, poverty, educational attainment, crime victimization and poor health. Survey and other data are used extensively to examine these conditions and their association with attributes of people. This project will provide methods to better determine the impact of effects associated with the h ....The role of households, neighbourhoods and networks in social statistics. Many issues affect the social progress of the country. Social research can determine the factors affecting issues such as unemployment, poverty, educational attainment, crime victimization and poor health. Survey and other data are used extensively to examine these conditions and their association with attributes of people. This project will provide methods to better determine the impact of effects associated with the household structure and other groups and social networks. The improved ability to assess the impact of these factors will have economic and social benefits. These benefits will arise from improved analysis leading to better decisions and improvements in the design of research studies improving their cost efficiency.Read moreRead less
Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and all ....Modelling the Choices of Individuals. Individuals make decisions daily and some of these decisions have wide-reaching and long-term consequences, such as choices among housing, public transport, electoral candidates and health care options. The principal aim of this project is to develop reliable and valid ways to model individual level choice processes. Once completed, this will provide insights into ways to aggregate sampled observations when population-level applications are required, and allow us to compare and test several competing theories of choice behaviour. This will enable us to make contributions to understanding and modelling human decision making in many fields ranging from marketing to medicine.Read moreRead less
Enhancing social research in Australia using dual-frame telephone surveys. The growing surge in mobile phones and mobile-phone only households has had a significant impact on the representativeness of social surveys and accuracy of social outcome measures. This project will develop methods for generating sampling lists of both types of telephone numbers to improve population coverage and accuracy of outcome measures.
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