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Field of Research : Statistical Theory
Socio-Economic Objective : Biological 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

    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: DP0556070

    Funder
    Australian Research Council
    Funding Amount
    $763,470.00
    Summary
    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.
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    Funded Activity

    Discovery Projects - Grant ID: DP0663757

    Funder
    Australian Research Council
    Funding Amount
    $42,728.00
    Summary
    Saddlepoint approximation, likelihood analysis and ancestral graphs for strong and weak natural selection, genetic drift and population subdivision. Building new research strength in theoretical population genetics and related statistical techniques will enhance Australia's capability in harnessing the power of post-genomic information. Sophisticated statistical techniques that make smart use of genetic data are being developed in this project. The extent to which natural selection and migrati .... Saddlepoint approximation, likelihood analysis and ancestral graphs for strong and weak natural selection, genetic drift and population subdivision. Building new research strength in theoretical population genetics and related statistical techniques will enhance Australia's capability in harnessing the power of post-genomic information. Sophisticated statistical techniques that make smart use of genetic data are being developed in this project. The extent to which natural selection and migration affect current genetic polymorphism on a population level can be quantified using these new methods. New modeling provides a rigorous foundation with which to construct inference techniques currently beyond computational approaches to the data. Assessing selective effects on genetic mutations associated with human disease will be a consequence of this new statistical methodology.
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    Funded Activity

    Discovery Projects - Grant ID: DP0450632

    Funder
    Australian Research Council
    Funding Amount
    $110,000.00
    Summary
    Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Pr .... Designing microarray experiments. Microarrays are powerful tools for surveying the expression levels of many thousands of genes simultaneously. They belong to the new genomics technologies which have important applications in the biological, pharmaceutical and agricultural sciences. There are many sources of uncertainty in microarray experimentation and good statistical designs are essential for ensuring that the effects of interest to scientists are accurately and precisely measured. This Project will develop novel designs for microarray experiments and focus on the advancement of topics crucial to Australia's success in technological research.
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    Funded Activity

    Discovery Projects - Grant ID: DP0342873

    Funder
    Australian Research Council
    Funding Amount
    $155,000.00
    Summary
    New and computationally feasible methods of constructing efficient and exact confidence limits from count data. Biological and health science data is commonly in the form of counts. The statistical analysis of such data should be (a) efficient i.e. it should not, in effect, throw away valuable data, (b) exact i.e. it should have precisely known statistical properties and (c) computationally feasible. Kabaila and Lloyd (1997-2001) have proposed and analysed a radically new method of confidence li .... New and computationally feasible methods of constructing efficient and exact confidence limits from count data. Biological and health science data is commonly in the form of counts. The statistical analysis of such data should be (a) efficient i.e. it should not, in effect, throw away valuable data, (b) exact i.e. it should have precisely known statistical properties and (c) computationally feasible. Kabaila and Lloyd (1997-2001) have proposed and analysed a radically new method of confidence limit construction which, for the first time, possesses all of these requirements. The purpose of the project is to establish further theoretical support for the new method, to develop efficient computational algorithms and to write easy-to-use computer programs for its practical use.
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