Discovery Projects - Grant ID: DP160102544

Funding Activity

Website
http://dataportal.arc.gov.au/NCGP/Web/Grant/Grant/DP160102544

Funding Status
Closed

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Funded Activity Summary

Frontiers in Bayesian methods for computationally intractable models. This project aims to develop new statistical methods for the analysis of computationally intractable models. Direct statistical analyses are often impossible when models are highly complex or too large, or when the dataset is too big. Using simpler models means that the wrong questions are being answered. Using less data is wasteful of information. This project aims to develop new methods for Bayesian statistical inference when standard methods are intractable. By allowing otherwise unavailable analyses, such techniques can enable and accelerate across-the-board research advances. Key expected innovations are new bases for sampling from computationally intractable distributions and novel distributed computing algorithms which could be applied to problems in health economics to infectious disease modelling, from climate extremes to road traffic modelling.

Funded Activity Details

Start Date: 01-01-2016

End Date: 31-12-2018

Funding Scheme: Discovery Projects

Funding Amount: $404,000.00

Funder: Australian Research Council

Research Topics

ANZSRC Field of Research (FoR)

Applied Statistics | Statistical Theory | Statistics |

ANZSRC Socio-Economic Objective (SEO)

Expanding Knowledge in the Mathematical Sciences

Other Keywords

Applied Statistics | Expanding Knowledge in the Mathematical Sciences | Statistical Theory | Statistics

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