Improved theory and practice in econometric modelling of nonlinear spatial time series. Modern Australia faces many challenges in economic and global climate changes, which require advanced statistical technologies in modeling and forecasting of econometric spatial time series data. This project will provide flexible models and methods that enable practitioners to more accurately measure and manage economic and climatic risks.
New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the ....New estimation and testing issues in nonlinear time series econometrics. The outcomes of this project will not only complement but also enhance the existing strengths of Australian researchers in the field of econometrics. The outcomes are also expected to help stabilise the national financial market for more accurate forecasts. It is also expected that the outcomes will provide novel models to respond to climate change and variability and to provide accurate warming estimates for improving the policy making process.Read moreRead less
Challenging econometric issues in nonlinear high-dimensional spatio-temporal prediction: theory and applications. This project will develop cutting-edge methodologies to break through challenging issues in nonlinear spatio-temporal econometric prediction. It will yield a new generation of prediction tools that enpower practitioners in Australia to produce more accurate forecasts, with more informed countermeasures to viarious economic and enviromental risks.
Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially impor ....Modelling mean and dispersion using fixed and random effects. The aims of the project are to develop methods for joint mean and dispersion modelling using fixed and random effects, in the generalized linear models context and for Gaussian longitudinal data. The significance is the more efficient, precise and appropriate analysis of data arising from many areas of application. The expected outcomes are therefore better methods of analysis, software to carry the analyses out, and potentially important results in applications.Read moreRead less
Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the mat ....Classification methods for providing personalised and class decisions. This project provides a novel approach to the clustering of multivariate samples on entities in a class that automatically matches the sample clusters across the entities, allowing for inter-sample variation between the samples in a class. The project aims to develop a widely applicable, mixture-model-based framework for the simultaneous clustering of multivariate samples with inter-sample variation in a class and for the matching of the clusters across the entities in the class. The project will use a statistical approach to automatically match the clusters, since the overall mixture model provides a template for the class. It will provide a basis for discriminating between different classes in addition to the identification of atypical data points within a sample and of anomalous samples within a class. Key applications include biological image analysis and the analysis of data in flow cytometry which is one of the fundamental research tools for the life scientist.Read moreRead less
Identifying The Critical Pathways Which Regulate Vertebrate Craniofacial Development
Funder
National Health and Medical Research Council
Funding Amount
$552,131.00
Summary
Understanding the genes which underlie human birth defects is of immense clinical importance. Our laboratory is a world-leader investigating a gene responsible for facial skeleton development, Grhl2. With our wide range of models, we will discover how Grhl2 works to ensure the face and skull develop properly during birth.
A new look at modelling population heterogeneity in econometric study. This research will advance existing quantitative techniques in economic study. New theoretical results will help enhance Australian research reputations. The innovative techniques developed in this project will be demonstrated to study labour force participation of people with disabilities in Australia. Findings of the empirical study will help governments in providing financial assistance to affected families and addressing ....A new look at modelling population heterogeneity in econometric study. This research will advance existing quantitative techniques in economic study. New theoretical results will help enhance Australian research reputations. The innovative techniques developed in this project will be demonstrated to study labour force participation of people with disabilities in Australia. Findings of the empirical study will help governments in providing financial assistance to affected families and addressing the issue of labour shortage in Australia. Furthermore the participation of a high profile international researcher will benefit the local research community and provide a research training opportunity for local postgraduate students.Read moreRead less
Discovery Early Career Researcher Award - Grant ID: DE160101565
Funder
Australian Research Council
Funding Amount
$330,000.00
Summary
Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodol ....Flexible data modelling via skew mixture models:challenges and applications. This project seeks to explore new models for handling data with non-normal features. Parametric distributions are fundamental to statistical modelling and inference. For centuries, the ‘normal’ distribution has been the dominant model for continuous data. However, real data rarely satisfy the assumption of normality. There is thus a strong demand for more flexible distributions. This project aims to develop new methodologies in finite mixture modelling using skew component distributions to provide better models for handling data with non-normal features (such as skewness, heavy/light tails, and multimodality). Applications may include security intrusion detection, clinical diagnosis and prognosis, and flow and mass cytometry.Read moreRead less
Modelling the capillary entrapment phenomena and integrity of geological reservoirs for clean energy, water and waste management technologies. This project will improve our understanding of non-linear flow and fracture phenomena in porous media which is prerequisite for the development of new emerging technologies targeting the reduction of the greenhouse gas emission and development of effective waste and water management solutions including coal gasification, in-situ storage of natural and non ....Modelling the capillary entrapment phenomena and integrity of geological reservoirs for clean energy, water and waste management technologies. This project will improve our understanding of non-linear flow and fracture phenomena in porous media which is prerequisite for the development of new emerging technologies targeting the reduction of the greenhouse gas emission and development of effective waste and water management solutions including coal gasification, in-situ storage of natural and non-hydrocarbon gases, underground disposal of hazardous wastes and vadose zone remediation. The project will result in a dramatic improvement of the predictive tools for traditional ground water management, irrigation and petroleum recovery applications. It has the strength to place Australia in the forefront of these technologies. Read moreRead less