Discovery Early Career Researcher Award - Grant ID: DE240101190
Funder
Australian Research Council
Funding Amount
$451,000.00
Summary
Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capa ....Innovating and Validating Scalable Monte Carlo Methods. This project aims to develop innovative scalable Monte Carlo methods for statistical analysis in the presence of big data or complex mathematical models. Existing approaches to scalable Monte Carlo are only approximate, and their inaccuracies are difficult to quantify. This can have a detrimental impact on data-based decision making. The expected outcomes of this project are scalable Monte Carlo methods that are more accurate, fast and capable of quantifying inaccuracies. Scientists and decision-makers will benefit from the ability to obtain timely, reliable insights for challenging applications.Read moreRead less
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. Read moreRead less
Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology wi ....Bayesian estimation of flexible spatial models with applications in medical imaging and econometric modeling. This project aims to develop statistical methodology for estimating flexible highly parameterised Bayesian spatial models. The flexible models examined will include regression, choice and time series models for data that is spatially registered. Spatial smoothing of parameters in the models will involve application of hierarchical spatial prior distributions. The resulting methodology will be applied to the analysis of medical imaging data and to the estimation of spatial econometric models of residential real estate prices. The expected outcomes include developments in the frontier framework of Bayesian computational estimation methodology, improved methods for medical image processing and estimation of high resolution spatial models of residential real estate prices in Australian metropolitan centres.Read moreRead less
Projecting Prevalence By Phase Of Care For Colorectal, Lung, Breast And Prostate Cancer In New South Wales
Funder
National Health and Medical Research Council
Funding Amount
$330,848.00
Summary
Cancer will become the top health issue in Australia due to the growth and ageing of the population. Accurate estimates of the numbers of people in the community at the different stages of their cancer journey (phases of care) now and in the future are required to plan for and provide adequate cancer care services. We will develop statistical models to estimate and predict cancer prevalence by phase of care for four major cancers in New South Wales.
Soft modes in glasses: chemical control of relaxation and mechanical response. The unusual dynamical and mechanical properties of viscous liquids and glasses underpins many existing and emerging technologies, from lubrication to the strength and fragility of bulk metallic glasses. An improved understanding of how macroscopic properties such as viscous flow, ductility and fracture emerge from the microscopic interactions between atoms and molecules will provide the enabling scientific knowledge f ....Soft modes in glasses: chemical control of relaxation and mechanical response. The unusual dynamical and mechanical properties of viscous liquids and glasses underpins many existing and emerging technologies, from lubrication to the strength and fragility of bulk metallic glasses. An improved understanding of how macroscopic properties such as viscous flow, ductility and fracture emerge from the microscopic interactions between atoms and molecules will provide the enabling scientific knowledge for exploiting the properties of such materials on the nanoscale. National expertise in this area will help establish and strengthen international collaboration with leading research institutes in the field.Read moreRead less
Estimation and Inference in Weakly Identified Models. Economic and social systems are made up of interacting components leading to complex structures that are difficult to predict and manage. Consequently policy analysis and decision-making must be informed by statistical analysis of data. In many situations the informational content of observations is minimal; examples of such situations are found in the areas of education, health, finance and various aspects of macroeconomic analysis. This pro ....Estimation and Inference in Weakly Identified Models. Economic and social systems are made up of interacting components leading to complex structures that are difficult to predict and manage. Consequently policy analysis and decision-making must be informed by statistical analysis of data. In many situations the informational content of observations is minimal; examples of such situations are found in the areas of education, health, finance and various aspects of macroeconomic analysis. This project aims to develop methods of estimation and inference that make more efficient use of the information available in data. This will lead to more precise statistical analyses, resulting in a clearer understanding of economic and social systems, and better informed policy analysis and decision-making.Read moreRead less
Immune-associated Genetic Variation And Autoimmune Disease.
Funder
National Health and Medical Research Council
Funding Amount
$1,346,721.00
Summary
Understanding the genes that underpin the immune system is vital for studying the causes and effects of diseases. In particular, autoimmune diseases are strongly associated with an individual having certain genetic types. We plan to develop methods to type immune-related genes very cheaply so they can be studied in very large samples. We will apply the methods we develop to genetic studies of psoriasis and multiple sclerosis, and make data and methods available to other scientists.