Website
http://dataportal.arc.gov.au/NCGP/API/grants/DP200102101
Funding Status
Active
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Funded Activity Summary
Advances in Sequential Monte Carlo Methods for Complex Bayesian Models. This project aims to develop efficient statistical algorithms for parameter estimation of complex stochastic models that currently cannot be handled. Parameter estimation is an essential component of mathematical modelling for answering scientific questions and revealing new insights. Current parameter estimation methods can be inefficient and require too much user intervention. This project will develop novel Bayesian algorithms that are optimally automated and efficient by exploiting ever-improving parallel computing devices. The new methods will allow practitioners to process realistic models, enabling new scientific discoveries in a wide range of disciplines such as biology, ecology, agriculture, hydrology and finance.Funded Activity Details
Start Date: 05-2020
End Date: 12-2024
Funding Scheme: Discovery Projects
Funding Amount: $390,000.00
Funder: Australian Research Council
Research Topics
ANZSRC Field of Research (FoR)
Applied Statistics | Statistical Theory | Statistics |
