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Socio-Economic Objective : Mathematical sciences
Research Topic : statistical methods
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  • Funded Activity

    Discovery Projects - Grant ID: DP0343811

    Funder
    Australian Research Council
    Funding Amount
    $108,000.00
    Summary
    Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstra .... Inference in partially non-stationary time series models. Economic theories typically specify the long-run relationship between economic variables. However, researchers usually examine the long-run features of the data by fitting a restrictive class of models using criteria that have only proven useful for short-term forecasting. In this project we consider alternative models and modelling strategies that are appropriate for the study of the long-run. We also develop computer intensive (bootstrap) methods, which will provide a much-needed improvement over the existing (asymptotic) methods for making inference about the long-run. Our research will lead to more reliable models for long-term planning in business, industry and government.
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    Funded Activity

    Discovery Projects - Grant ID: DP0984399

    Funder
    Australian Research Council
    Funding Amount
    $387,943.00
    Summary
    Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The .... Vector ARMA Models and Macroeconomic Modelling: Some New Methodology and Algorithms. Economic variables are strongly related to each other, as well as being strongly related to their recent history. As a result, good dynamic multivariate models are crucial for effective policy making and forecasting in areas of vital national importance such as monetary and fiscal policy, environmental policy and tourism. Our project advances the frontiers of knowledge in multivariate time series modelling. The outcome of this project will be immediately useful for macroeconomic policy makers such as the Reserve Bank of Australia and the Treasury, and for industry bodies such as Tourism Australia.
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    Funded Activity

    Discovery Projects - Grant ID: DP0881310

    Funder
    Australian Research Council
    Funding Amount
    $235,000.00
    Summary
    Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), .... Complex data, model selection and bootstrap inference. The project will provide new statistical methods and associated software for the analysis and modelling of complex data, as well as quality research training. This project will benefit researchers in statistics and users of statistics who encounter the complex data considered in this project and who need to model and make inferences from these data. Since these kinds of data arise in many areas (such as medicine, genetics, chemistry etc), Australia and Australian industry will ultimately benefit from the proposed research. The strengthening of international link and the training of highly trained research scientists in an area of national importance will also benefit Australia.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559135

    Funder
    Australian Research Council
    Funding Amount
    $269,000.00
    Summary
    Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the r .... Bootstrap methods for data with multiple errors. This project will provide new methods for data analysis and quality research training. The results will benefit researchers in statistics and users of statistics who encounter data with multiple errors and who need to make inferences from these data. The many areas from which such data arise (including medicine, genetics, chemistry, education, social surveys etc) mean that Australia and Australian Industry will also ultimately benefit from the research. The strengthening of international links and the training of highly trained researchers will also benefit the Australian community.
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    Funded Activity

    Discovery Projects - Grant ID: DP0986563

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig .... Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.
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    Funded Activity

    Linkage Projects - Grant ID: LP0562008

    Funder
    Australian Research Council
    Funding Amount
    $446,599.00
    Summary
    Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of .... Investment Approaches and Applications in Financial Markets: Evolutionary Kernel Based Subset Time-Series Using Semi-Parametric Approaches. The project will develop new investment assessments based on subset time-series modeling. Innovative evolutionary kernel smoothing algorithms using semi-parametric approaches will be introduced. The project will make three important applications of this modeling in financial markets: a) benchmarking and evaluation of inflation-indexed bonds; b) evaluation of the performance of global diversified investment funds; and c) prediction to provide early warning of the emergence of destabilising deflation or inflation. These three applications will lead to improved risk management practices and investment performance. Recursive algorithms will provide new statistical methods to study investment asset price movements and market volatility.
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    Funded Activity

    Discovery Projects - Grant ID: DP1092801

    Funder
    Australian Research Council
    Funding Amount
    $300,000.00
    Summary
    The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of .... The improvement of climate change investigations by developing and applying innovative evolutionary subset time series modelling using semi-parametric sparse-patterned approaches. With an estimated US$6.98 trillion loss indicated in the Stern review, severe climate change will make world climate conditions harsher and more likely include large natural climate disasters. The health of the Australian economy is critically dependent on decisions of environmental managers. However, most problems of complexity arising in climate change involve issues on which we do not possess a deep understanding. This project draws upon a set of inter-disciplinary concepts and models centred in neural networks that enable us to advance our understanding of complexity, leading to superior quantitative tools and models to allow for improved environmental decision-making.
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    Funded Activity

    Linkage Projects - Grant ID: LP0989811

    Funder
    Australian Research Council
    Funding Amount
    $255,000.00
    Summary
    Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in th .... Investment approaches and opportunities in renewable energy and financial resource markets, using semi-parametric approaches to evolutionary subset time-series lattice-ladder modelling. The project findings will help Australian exporters and importers understand and manage energy and resource price risks more effectively. The investment community will benefit through selecting optimal asset allocations and enhancing value to investors. It will also benefit many other agencies, particularly in the service industries. It is not well recognised that in developed countries, including Australia, the financial service and related sectors account for more than 60 percent of economic activity and employment, so it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial service and related sectors.
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    Funded Activity

    Discovery Projects - Grant ID: DP0559465

    Funder
    Australian Research Council
    Funding Amount
    $333,000.00
    Summary
    Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a hig .... Asymptotic Geometric Analysis and Learning Theory. Learning Theory is used in various real-world applications in diverse research areas, ranging from Biology (e.g. DNA sequencing) to Information Sciences. Therefore, having a deep understanding of fundamental questions in Learning Theory, and in particular, pin-pointing the parameters that make a learning problem hard would have a significant practical impact. This projects aims to achieve this goal, and in addition, we expect it would have a high theoretical value, as the questions we shall address are of independent interest to pure mathematicians.
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    Funded Activity

    Linkage Projects - Grant ID: LP0883801

    Funder
    Australian Research Council
    Funding Amount
    $390,000.00
    Summary
    The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormou .... The improvement of investment approaches by developing and applying bootstrap methods to innovative evolutionary kernel-based subset time-series modelling. With over $1 trillion of investors' monies in the hands of fund managers, the importance of efficient investment decisions across all industry sectors is self evident. Even if the modest target of systematically improving decision making by 1 or 2 % is set, the aggregate economic benefit achieved, given the compounding effects will be enormous. Any developed or developing country will profit from such advanced decision-making approaches. Therefore it is critical that more sophisticated statistical methods be established, and practical applications conducted, in order to advance the understanding of complexity management in the financial investment and other relevant sectors.
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