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Field of Research : Statistics
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  • Funded Activity

    ARC Centres Of Excellence - Grant ID: CE140100049

    Funder
    Australian Research Council
    Funding Amount
    $20,000,000.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0344092

    Funder
    Australian Research Council
    Funding Amount
    $215,000.00
    Summary
    Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic. The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunicati .... Problems of identification and inference for 'non-standard' models in complex systems with special reference to finance and teletraffic. The project is concerned with 'non-standard' models needed to deal with complex systems, such as those exhibiting scaling and fractal properties. There is a focus on methods for dealing with heavy tailed distributions and long range dependent observations, for which most standard statistical methods break down, and on applications in finance and telecommunications. An important part of the project concerns model validation for Heyde's fractal activity time geometric Brownian motion model, a candidate minimal description risky asset model to replace the geometric Brownian motion paradigm.
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