Cited By
View all- Gerhards CPereverzyev STkachenko P(2017)A parameter choice strategy for the inversion of multiple observationsAdvances in Computational Mathematics10.1007/s10444-016-9477-943:1(101-112)Online publication date: 1-Feb-2017
Aggregation of forecasts from multiple simulation models
Pages 533 - 542
Abstract
When faced with output from multiple simulation models, a decision maker must aggregate the forecasts provided by each model. This problem is made harder when the models are based on similar assumptions or use overlapping input data. This situation is similar to the problem of expert judgment aggregation where experts provide a forecast distribution based on overlapping information, but only samples from the output distribution are obtained in the simulation case. We propose a Bayesian method for aggregating forecasts from multiple simulation models. We demonstrate the approach using a climate change example, an area often informed by multiple simulation models.
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- Aggregation of forecasts from multiple simulation models
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Information & Contributors
Information
Published In
December 2013
4386 pages
ISBN:9781479920778
- General Chair:
- Raymond R. Hill,
- Program Chair:
- Michael E. Kuhl
Sponsors
- IIE: Institute of Industrial Engineers
- INFORMS-SIM: Institute for Operations Research and the Management Sciences: Simulation Society
- ASA: American Statistical Association
- SIGSIM: ACM Special Interest Group on Simulation and Modeling
- SCS: Society for Modeling and Simulation International
- ASIM: Arbeitsgemeinschaft Simulation
- IEEE/SMCS: Institute of Electrical and Electronics Engineers/Systems, Man, and Cybernetics Society
- NIST: National Institute of Standards & Technology
Publisher
IEEE Press
Publication History
Published: 08 December 2013
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WSC '13
Sponsor:
- IIE
- INFORMS-SIM
- ASA
- SIGSIM
- SCS
- ASIM
- IEEE/SMCS
- NIST
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Overall Acceptance Rate 3,413 of 5,075 submissions, 67%
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Cited By
View all- Gerhards CPereverzyev STkachenko P(2017)A parameter choice strategy for the inversion of multiple observationsAdvances in Computational Mathematics10.1007/s10444-016-9477-943:1(101-112)Online publication date: 1-Feb-2017
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