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Grant Award View - GA68557
Loss-based Bayesian Prediction
GA ID:
GA68557
Agency:
Australian Research Council
Approval Date:
20-Dec-2019
Publish Date:
6-Jan-2020
Category:
Humanities, Arts and Social Sciences (HASS) Research
Grant Term:
19-Jun-2020 to 18-Jun-2024
Original: 1-Jan-2020 to 31-Dec-2022
Value (AUD):
$393,000.00
(GST inclusive where applicable)
Variations:
- GA68557-V4 - Variation to Grant (4-Jul-2023 )
- GA68557-V3 - Variation to Grant (20-Oct-2021 )
- GA68557-V2 - Variation to Grant (2-Aug-2021 )
- GA68557-V1 - Variation to Grant (25-May-2021 )
One-off/Ad hoc:
No
Aggregate Grant Award:
No
PBS Program Name:
ARC 19/20 Discovery
Grant Program:
Discovery Projects
Grant Activity:
Loss-based Bayesian Prediction
Purpose:
This project proposes a new paradigm for prediction. Using state-of-the-art computational methods, the project aims to produce accurate, fit for purpose, predictions which, by design, reduce the loss incurred when the prediction is inaccurate. Theoretical validation of the new predictive method, without reliance on knowledge of the correct statistical model, is an expected outcome, as is an extensive numerical assessment of its performance in empirical settings. The new paradigm should produce significant benefits for all fields in which the consequences of predictive inaccuracy are severe. Problems that lead to substantial economic, financial or environmental loss if predictions are incorrect will be given particular attention.
GO ID:
GO Title:
Discovery Projects for funding commencing in 2020
Internal Reference ID:
DP20 Round 1
Selection Process:
Targeted or Restricted Competitive
Confidentiality - Contract:
No
Confidentiality - Outputs:
No
Grant Recipient Details
Recipient Name:
Monash University
Recipient ABN:
12 377 614 012
Grant Recipient Location
Suburb:
MULGRAVE
Town/City:
MULGRAVE
Postcode:
3170
State/Territory:
VIC
Country:
AUSTRALIA
Grant Delivery Location
State/Territory:
VIC
Postcode:
3170
Country:
AUSTRALIA