Min/Max Autocorrelation Factors in Time Series Studies of the Adverse Health Effects of Ozone. The annual health costs associated with exposure to air pollution in Australia have been estimated at between $3 and 5.3 billion. Given these costs, it is vital to conduct research that ensures public health officials and policy makers stay fully informed of Australia’s air pollution problem. The project proposes to address this need by developing methodology to detect trends in air pollution concentra ....Min/Max Autocorrelation Factors in Time Series Studies of the Adverse Health Effects of Ozone. The annual health costs associated with exposure to air pollution in Australia have been estimated at between $3 and 5.3 billion. Given these costs, it is vital to conduct research that ensures public health officials and policy makers stay fully informed of Australia’s air pollution problem. The project proposes to address this need by developing methodology to detect trends in air pollution concentrations and reduce measurement error in recorded air pollution concentrations. This will enable relevant authorities to produce more accurate estimates of air pollution health costs and implement more appropriate pollution regulations and health warnings.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
Air pollution: do modern statistical model selection techniques make the silent killer speak too loud? Air pollution is estimated to cause 2400 deaths annually in Australia with an associated cost to the community of $17.2 billion. The outcomes of this project will enable an improved understanding of the association between air pollution and mortality in Australia, thereby allowing government, public health authorities, and regulatory agencies to implement better air pollution standards and pro ....Air pollution: do modern statistical model selection techniques make the silent killer speak too loud? Air pollution is estimated to cause 2400 deaths annually in Australia with an associated cost to the community of $17.2 billion. The outcomes of this project will enable an improved understanding of the association between air pollution and mortality in Australia, thereby allowing government, public health authorities, and regulatory agencies to implement better air pollution standards and provide more informed advice to the public on the necessity of avoiding exposure to air pollutants. These two outcomes are particularly important given Australia's ageing population and the fact that the elderly are among those most susceptible to harm from air pollution exposure.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
Predicting Roll Angular Motion. The roll angular motion, or RAM, of a ship denotes its oscillation about its longitudinal axis, primarily caused by wave motion. The ability to predict RAM is of significant practical utility. For example, in defence-related work it plays a role in determining accuracy of weapons systems. We suggest a technique for predicting RAM. Our method borrows from both parametric and nonparametric statistics, in that a sinusoidal model is fitted to data but only over a ....Predicting Roll Angular Motion. The roll angular motion, or RAM, of a ship denotes its oscillation about its longitudinal axis, primarily caused by wave motion. The ability to predict RAM is of significant practical utility. For example, in defence-related work it plays a role in determining accuracy of weapons systems. We suggest a technique for predicting RAM. Our method borrows from both parametric and nonparametric statistics, in that a sinusoidal model is fitted to data but only over a short time interval. We show how to both assess and correct error. In particular, we propose methods for attaching probabilities to the accuracy of predictions.Read moreRead less
ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this ....ARC Centre of Excellence for Mathematical and Statistical Frontiers of Big Data, Big Models, New Insights. In today's world, massive amounts of data in a variety of forms are collected daily from a multitude of sources. Many of the resulting data sets have the potential to make vital contributions to society, business and government, as well as impact on international developments, but are so large or complex that they are difficult to process and analyse using traditional tools. The aim of this Centre is to create innovative mathematical and statistical models that can uncover the knowledge concealed within the size and complexity of these big data sets, with a focus on using the models to deliver insight into problems vital to the Centre's Collaborative Domains: Healthy People, Sustainable Environments and Prosperous Societies.Read moreRead less