Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models ....Advanced Mixture Models for the Analysis of Modern-Day Data. Extracting key information from huge data sets is critical to the scientific successes of the future. This project will develop novel mixture models that can be used directly to analyse complex and high-dimensional data sets that may consist of thousands of variables observed on only a limited number of entities. In order to handle the challenging problems arising in the latter situation. This project develops mixtures of factor models with options for skew distributions that can be used to effectively analyse such data. Key applications include the domains of bioinformatics, biostatistics, business, data mining, economics, finance, image analysis, marketing, and personalised medicine, among many others.Read moreRead less
Joint clustering and matching of multivariate samples across objects. The project will provide a novel and very effective approach to the clustering of multivariate samples on objects, say patients, that automatically matches the sample clusters across the objects. A key application is the matching of biologically relevant cell subtypes across patients for use in the study and the clinical diagnosis and prognosis of cancer.
Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increas ....Expanding the role of mixture models in statistical analyses of big data. This project aims to develop theoretical procedures to scale inference and learning algorithms to analyse big data sets. It will develop analytic tools and algorithms to analyse big data sets which classical methods of inference cannot analyse directly due to the data’s complexity or size. This will accelerate the progress of scientific discovery and innovation, leading, for example, to new fields of inquiry; to an increase in understanding from studies on human and social processes and interactions; and to the promotion of economic growth and improved health and quality of life. Such applications should lead to breakthrough discoveries and innovation in science, engineering, medicine, commerce, education and national security.Read moreRead less
A new approach to fast matrix factorization for the statistical analysis of high-dimensional data. Some form of dimension reduction is essential in order to extract meaningful information from huge data sets. For this purpose we provide a novel and very fast approach to the factorization of the data matrix. It has wide applicability for improving the quality and validity of research in science and medicine and in most industries in Australia.
Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based stati ....Large-Scale Statistical Inference: Multiple Testing. Multiple testing procedures are among the most important statistical tools for the analysis of modern data. This project aims to develop new methods for providing more powerful simultaneous tests while controlling the proportion of false positive conclusions. They are proposed to be derived by the novel pooling of information in individual attribute based contrasts to produce a Weighted Individual attribute-Specific Contrast (WISC) based statistic. They will also exploit contextual information. They are expected to be of direct application to the problem of testing for no differences between two or more classes, as in the detection of differential expression in bioinformatics. Other key applications are expected to include biomedicine, economics, finance, genetics, and neuroscience.Read moreRead less
Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore co ....Relaxed correctness criteria for modern multi-core architectures. This project seeks to lay groundwork for fully exploiting the potential of multicore computers. Multicore computers have become ubiquitous over the last decade, now being standard in everything from laptops to mobile phones. Their benefits are clear – better performance leading to more sophisticated applications. Key to ensuring those benefits are complex, and often subtle, algorithms that exploit the parallelism that multicore computers offer. This project aims to lay foundations for extending those benefits to applications where high reliability is a concern. It plans to do so by developing theoretical results about the correctness of algorithms on standard multicore computers, and practical tools and techniques to help programmers of multicore computers to better understand the behaviour of their code.Read moreRead less
Income insecurity in Australia: who is feeling the pinch and why? This project aims to measure and investigate the drivers of income insecurity in Australia. It will provide an evaluation of whether income growth is sufficient to compensate for any welfare loss due to higher income risk and the effectiveness of government taxes and transfers in alleviating income risks for different population sub-groups.
New Developments for Bayesian statistical models and computational methods. Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with l ....New Developments for Bayesian statistical models and computational methods. Bayesian methods of statistical analysis provide a flexible theory for addressing inference in the presence of uncertainty. Consequently Bayesian methods have enabled scientific discovery in areas characterised as complex systems where new developments in modelling and computational methods have been crucial. Significant barriers to further success involve challenges in formulating and validating models, dealing with large data sets, and developing efficient computational methods. The principal aim of this project is to develop new Bayesian modelling and computational methodology which address these challenges with broad application.Read moreRead less
Towards Engineering Behavioural Research Design Systems. Behavioural research is a significant component of the annual spend in Australia on research and development. It is contended that 'best practice' behavioural research methods can be more systematised, transparent and visible; facilitating more complex, integrated and holistic research designs; and thereby, more cumulative and comparable results; thus enabling increased rigor, higher productivity and lower risk than have generally been the ....Towards Engineering Behavioural Research Design Systems. Behavioural research is a significant component of the annual spend in Australia on research and development. It is contended that 'best practice' behavioural research methods can be more systematised, transparent and visible; facilitating more complex, integrated and holistic research designs; and thereby, more cumulative and comparable results; thus enabling increased rigor, higher productivity and lower risk than have generally been the experience historically. This project proposes the formal conceptualisation and modelling of behavioural science research methods, by adapting them to the research design, the well understood concepts, tools and techniques of Information Systems design. Results are expected to form the conceptual basis of 'Research Design Systems.'Read moreRead less
Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identi ....Statistical Methods for Discovering Ribonucleic acids (RNAs) contributing to human diseases and phenotypes. Identifying the causative genetic factors involved in quantitative phenotypes and diseases is a major goal of biology in the 21st century and beyond. A crucial step towards this goal is identifying and classifying the functional non-protein-coding Ribonucleic acids (RNAs) encoded in the human genome. This project will make major contributions to international efforts in this area by identifying RNA molecules that contribute to quantitative phenotypes including susceptibility to disease. As such, it will directly benefit fundamental science via the discovery and classification of new molecules. Indirectly, it will lead to breakthroughs in biology, and consequently to major medical and pharmaceutical advances in the diagnosis and treatment of genetic disease.Read moreRead less