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Australian State/Territory : NSW
Socio-Economic Objective : Biological sciences
Research Topic : statistical analysis
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  • Funded Activity

    Discovery Projects - Grant ID: DP0667069

    Funder
    Australian Research Council
    Funding Amount
    $316,000.00
    Summary
    Efficient Estimation of Statistical Models with Many Parameters. Statistical models are used extensively in business, engineering and the sciences to describe the behavior of systems subject to uncertainty. There are often many unknowns in such models and relatively little data to estimate them. The object of the research is to develop methods that make these statistical models practical to use. The research team will apply the methodology to solve problems in economics, finance, marketing and t .... Efficient Estimation of Statistical Models with Many Parameters. Statistical models are used extensively in business, engineering and the sciences to describe the behavior of systems subject to uncertainty. There are often many unknowns in such models and relatively little data to estimate them. The object of the research is to develop methods that make these statistical models practical to use. The research team will apply the methodology to solve problems in economics, finance, marketing and the analysis of gene expression data. The project will also train doctoral and postdoctoral students and enhance Australia's reputation for research excellence in the Statistical and Mathematical Sciences.
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    Funded Activity

    Discovery Projects - Grant ID: DP0664970

    Funder
    Australian Research Council
    Funding Amount
    $119,657.00
    Summary
    Trans-dimensional and Approximate Bayesian Computation. Many applied scientists in Australia, particularly those in the biological, medical and environmental sciences are now interested in incorporating Bayesian statistical methodologies into their research. The development of more generic and efficient Bayesian statistical methods will not only benefit applied statisticians but also the more occasional users of statistics in other disciplinary areas. The success of this project will enhance Au .... Trans-dimensional and Approximate Bayesian Computation. Many applied scientists in Australia, particularly those in the biological, medical and environmental sciences are now interested in incorporating Bayesian statistical methodologies into their research. The development of more generic and efficient Bayesian statistical methods will not only benefit applied statisticians but also the more occasional users of statistics in other disciplinary areas. The success of this project will enhance Australia's reputation as a strong contributor to the development of Bayesian methodologies. Two PhD students will also be provided training in computational Bayesian statistics.
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    Funded Activity

    Special Research Initiatives - Grant ID: SR0354716

    Funder
    Australian Research Council
    Funding Amount
    $10,000.00
    Summary
    Energetically Open Systems Research Network Study. Conceptual frameworks arising in the physical sciences, such as non-equilibrium statistical mechanics and thermodynamics, synergetics, chaos and dynamical systems theory, are seminal in the emerging science of complexity. This study will lay the groundwork for a network to link Australian and overseas research on these fundamental concepts, and their application within the context of entropy-producing systems vital to the long-term sustainabilit .... Energetically Open Systems Research Network Study. Conceptual frameworks arising in the physical sciences, such as non-equilibrium statistical mechanics and thermodynamics, synergetics, chaos and dynamical systems theory, are seminal in the emerging science of complexity. This study will lay the groundwork for a network to link Australian and overseas research on these fundamental concepts, and their application within the context of entropy-producing systems vital to the long-term sustainability of the earth - oceans, atmosphere, biosphere, CO2-free energy production, space and solar environment. The network would facilitate the development of young investigators and be linked into wider complex systems networks such as the CSIRO Centre for Complex Systems Science.
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    Funded Activity

    Linkage Projects - Grant ID: LP0882396

    Funder
    Australian Research Council
    Funding Amount
    $179,047.00
    Summary
    Computer simulation techniques to reduce the incidence of femoral fracture after hip replacement surgery. Australia's ageing population is driving an increase of 5% to 10% a year in the number of primary total hip replacements. We will move beyond conventional surgical techniques, to deliver the science for an accurate, reliable computer-based system that is significantly more accurate and reliable. Optimising implant selection criteria to better match patients' activity levels and bone physiolo .... Computer simulation techniques to reduce the incidence of femoral fracture after hip replacement surgery. Australia's ageing population is driving an increase of 5% to 10% a year in the number of primary total hip replacements. We will move beyond conventional surgical techniques, to deliver the science for an accurate, reliable computer-based system that is significantly more accurate and reliable. Optimising implant selection criteria to better match patients' activity levels and bone physiology and minimise revision rates; this has major implications for the national health budget and patients' quality of life. Our advances will allow the implementation of improved surgical techniques that minimise the risk of implant related bone failure.
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    Funded Activity

    Discovery Projects - Grant ID: DP0344762

    Funder
    Australian Research Council
    Funding Amount
    $165,000.00
    Summary
    Parameterized Algorithm Design and Complexity Analysis: New Methods and Strategic Applications in the FPT Algorithmic Server Project. A fundamental discovery of the first decades of computer science is that completely efficient (polynomial time) algorithms probably do not exist for thousands of natural computational problems. The project will result in new methods for designing and analyzing algorithms for hard problems with natural parameters, and in improved algorithms for these problems.
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