Fast approximate inference methods for flexible regression

Collaborating Organisation

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• The University Of Sydney  Research Organization
• University of Illinois  Research Organization

Scheme

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• Discovery Projects

Abstract

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• Flexible regression is now a mainstay of statistical analysis of complex data sets. This project will gear up flexible regression for larger problems brought about by the current era of rapid technological change. It will draw upon approximate inference methods developed in Computer Science, leading to new statistical methodology for fast analyses. It will also develop novel statistical theory and new methodology for neuroimage data. The project will allow analyses of large data sets that would not even be attempted using currently available methods, opening up a wide range of new applications.

Date/time Interval

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• 2011

Research Areas

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• 010401 - APPLIED STATISTICS
• 010405 - STATISTICAL THEORY
• 010499 - STATISTICS NOT ELSEWHERE CLASSIFIED

Awarded By

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• Australian Research Council (ARC) 

Contributor

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• Wand, M P. - Chief Investigator

Geographic Focus

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• Australia 
• United States of America 

Geographic Focus

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• Australia  Country
• United States of America  Country

Sponsor Award Id

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• DP110100061

Local Award Id

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• 11730