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
Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give ins ....Bayesian Statistical Inference for Implicitly defined Probability Models. Bayesian statistics has recently been used to provide solutions for a large number of hitherto intractable problems in science and technology. The success of Bayesian statistics has mainly been due to the application of so-called Markov chain Monte Carlo computational techniques. We aim to improve these algorithms, by providing fast, simple and efficient computational implementations. We will use the results to give insight by carefully quantifying and modelling uncertainty for such topics as the transmission rate of infectious diseases, the spatial distribution of plant and animal species, investigating biological theory for the genome of a virus, and changes in human fertility.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
Theory and application of computer-intensive, nonparametric statistical methods. The availability of increasingly powerful computing equipment continues to have a dramatic impact on statistical methods and thinking. These developments, combined with new technologies for generating data, are driving substantial changes in statistics, ranging from the types of problems being solved to the sorts of methods used to solve them. Both the problems and their solutions are of substantial national and c ....Theory and application of computer-intensive, nonparametric statistical methods. The availability of increasingly powerful computing equipment continues to have a dramatic impact on statistical methods and thinking. These developments, combined with new technologies for generating data, are driving substantial changes in statistics, ranging from the types of problems being solved to the sorts of methods used to solve them. Both the problems and their solutions are of substantial national and community benefit. They will be the subject of high-level research supported by this proposal. Read moreRead less
Nonparametric Statistical Methods -- New Directions, Theory and Applications. The research program will take Australia to the forefront of contemporary work in nonparametric statistics, and assist greatly in the training of a new generation of Australian statistical scientists. It will contribute significantly to restoring the health of this strategically important field, in Australian universities and in the nation more generally. The projects outlined in the proposal address problems arising ....Nonparametric Statistical Methods -- New Directions, Theory and Applications. The research program will take Australia to the forefront of contemporary work in nonparametric statistics, and assist greatly in the training of a new generation of Australian statistical scientists. It will contribute significantly to restoring the health of this strategically important field, in Australian universities and in the nation more generally. The projects outlined in the proposal address problems arising in astronomy, economics, engineering, defence, health and image analysis, but the potential areas of impact are broader even than this. This diversity illustrates the extraordinary potential, and strategic significance, of statistics to Australia. Read moreRead less
Statistical Analysis of Some Partially Observed Processes Arising in Ecological Research. The expected outcomes of this project are the provision of statistical methods to draw important information from samples from wild animal populations and the training of researchers to conduct high quality statistical ecological research. The national benefit lies on the availability of the developed techniques and researchers from this project to the society for finding better ways of managing Australia's ....Statistical Analysis of Some Partially Observed Processes Arising in Ecological Research. The expected outcomes of this project are the provision of statistical methods to draw important information from samples from wild animal populations and the training of researchers to conduct high quality statistical ecological research. The national benefit lies on the availability of the developed techniques and researchers from this project to the society for finding better ways of managing Australia's ecological systems and making Australia environmentally sustainable.Read moreRead less
Theory and applications of Bayesian and likelihood analyses for finite mixture, random effect and multinomial models. The expected outcomes of the project are: to establish the scientific
value of modern Bayesian methods for statistical inference in a wider
range of applications than previously available, to contribute to the greater unification of the current theories of statistical inference which are to some extent in conflict, and to provide a set of Bayesian analytic tools implemented in ....Theory and applications of Bayesian and likelihood analyses for finite mixture, random effect and multinomial models. The expected outcomes of the project are: to establish the scientific
value of modern Bayesian methods for statistical inference in a wider
range of applications than previously available, to contribute to the greater unification of the current theories of statistical inference which are to some extent in conflict, and to provide a set of Bayesian analytic tools implemented in widely available, free and open-source statistical software.
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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
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
Statistical methodology for events on a network, with application to road safety. This project develops new methods to analyse road traffic accident rates, aiming to identify accident black spots and to develop an evidence base for future road design and road safety management. These methods can be applied to other types of events on a network of roads, railways, rivers, electrical wires, communication networks or airline routes.