Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), ....Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), Australia and Australian industry will ultimately benefit from the proposed research. The strengthening of international link and the training of highly trained research scientists in an area of national importance will also benefit Australia.Read moreRead less
Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering ap ....Parallel and Distributed Machine Learning - Smart Data Analysis in the Multicore Era. In large data centres our research will lead to reduced energy consumption by using graphics cards which have a much better computation to power ratio than traditional processors. On desktop computers, it will make machine learning practical by enabling efficient algorithms for spam filtering and content analysis. On networked systems it will lead to distributed inference, caching and collaborative filtering applications which will both reduced the bandwidth required and make the internet safer for users. Finally, it will enable rapid deployment of sensor networks for monitoring and detection, such as for environmental monitoring and safeguarding Australia's borders.Read moreRead less
Theory and Applications of Computer-Intensive Statistical Methods. The availability of powerful computing equipment has had a dramatic impact on statistical methods and thinking. It has motivated development of novel approaches to data analysis, whose conception
and appreciation, even their application, often demand sophisticated and complex theoretical methods. In this context, the project will develop new approaches to solving non-standard statistical problems. These techniques will eithe ....Theory and Applications of Computer-Intensive Statistical Methods. The availability of powerful computing equipment has had a dramatic impact on statistical methods and thinking. It has motivated development of novel approaches to data analysis, whose conception
and appreciation, even their application, often demand sophisticated and complex theoretical methods. In this context, the project will develop new approaches to solving non-standard statistical problems. These techniques will either have direct application to solving practical problems of national or community concern, or provide a better understanding of the nature of such problems.Read moreRead less
Expenditure needs and drawdown of retirement savings during later life: how important are demographic factors and financial resources? Projections of expenditure patterns in retirement which allow for population heterogeneity will provide individuals with a better appreciation of their income needs and their savings requirements for a comfortable retirement. It will also enable financial institutions to develop products which better target retirees' needs over the course of retirement, and in ad ....Expenditure needs and drawdown of retirement savings during later life: how important are demographic factors and financial resources? Projections of expenditure patterns in retirement which allow for population heterogeneity will provide individuals with a better appreciation of their income needs and their savings requirements for a comfortable retirement. It will also enable financial institutions to develop products which better target retirees' needs over the course of retirement, and in addition it will enable improved assessment of aspects of Government income support policy. Specifically, understanding the complex interactions between private and public pensions, and concession card receipt upon expenditure behaviour, will enable more accurate costings of the public support of elderly families as Australia's population ages. Read moreRead less
NONPARAMETRIC STATISTICS. Nonparametric statistical methods are techniques that implicitly choose statistical models from exceptionally large and highly adaptive classes. The project aims to develop innovative and practicable nonparametric methods in four areas: Statistical Smoothing, Data Mining, Mixture Methods and Robust Inference. The significance of the work lies in its novelty, the breadth of its practical motivation, and its position at the leading edge of contemporary work in statisti ....NONPARAMETRIC STATISTICS. Nonparametric statistical methods are techniques that implicitly choose statistical models from exceptionally large and highly adaptive classes. The project aims to develop innovative and practicable nonparametric methods in four areas: Statistical Smoothing, Data Mining, Mixture Methods and Robust Inference. The significance of the work lies in its novelty, the breadth of its practical motivation, and its position at the leading edge of contemporary work in statistics. Expected outcomes include new technologies for data analysis.Read moreRead less
New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release o ....New mathematical and statistical methods that inform the control of infectious disease outbreaks. Emerging infectious diseases are an ever-present threat to our community, as highlighted by the recent SARS epidemic and current fears concerning avian influenza. The research proposed by this project will help policy makers implement effective border control and outbreak control against a variety of emerging and re-emerging infectious diseases, including SARS, influenza and the deliberate release of an infectious disease such as smallpox. The project will enhance preparedness through a better understanding of the relative merits of different control strategies, and provide new methodology that can dynamically guide border and outbreak control in the midst of an outbreak by making effective use of data. Read moreRead less
Linkage Infrastructure, Equipment And Facilities - Grant ID: LE0453870
Funder
Australian Research Council
Funding Amount
$102,900.00
Summary
Social science advanced data modelling, analysis and visualisation facility. This is an integrated facility for advanced social science data analysis, modelling and visualisation located at The University of Queensland. The collaborating institutions are UQ, ANU and Griffith University. The facility promotes deep collaborations between social scientists and quantitative methodologists (statisticians, biostatisticians, econometricians) to enable leading edge quantitative analyses of survey, spati ....Social science advanced data modelling, analysis and visualisation facility. This is an integrated facility for advanced social science data analysis, modelling and visualisation located at The University of Queensland. The collaborating institutions are UQ, ANU and Griffith University. The facility promotes deep collaborations between social scientists and quantitative methodologists (statisticians, biostatisticians, econometricians) to enable leading edge quantitative analyses of survey, spatial and population data, new developments in quantitative methodology for statistical modelling and data visualisation, enhanced international research linkages and advanced postgraduate research training.Read moreRead less
Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the r ....Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the research. The strengthening of international links and the training of highly trained researchers will also benefit the Australian community.Read moreRead less
Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there ....Seasonal adjustment using disaggregated short time span data. Seasonally adjusted economic and social times series are vital information used by governments and businesses in decision making. This project will develop statistical methods to estimate and remove seasonal factors from economic and social time series using finely disaggregated data for a relatively small number of time periods. This will enable better and quicker estimation of seasonal factors when new series are introduced or there a major changes to existing series, improving the analysis of such series and the decisions based on them.Read moreRead less