Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology

DOI10.1016/j.csda.2018.03.004zbMath1469.62053OpenAlexW2790533601WikidataQ62899308 ScholiaQ62899308MaRDI QIDQ1662873

Mahasen B. Dehideniya, Christopher C. Drovandi, James M. McGree

Publication date: 20 August 2018

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://eprints.qut.edu.au/97824/1/EBDforDBMILE_eprint.pdf

zbMATH Keywords

parameter estimationmutual informationapproximate Bayesian computationmodel discriminationDs-optimalitycoordinate exchange algorithmzero-one utility

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Epidemiology (92D30) Applications of statistics to biology and medical sciences; meta analysis (62P10) Optimal statistical designs (62K05)

Related Items (5)

Optimal Bayesian design for model discrimination via classification ⋮ Designing group dose-response studies in the presence of transmission ⋮ Improving the efficiency of fully Bayesian optimal design of experiments using randomised quasi-Monte Carlo ⋮ Identification of the relative timing of infectiousness and symptom onset for outbreak control ⋮ Bayesian design of experiments for intractable likelihood models using coupled auxiliary models and multivariate emulation

Uses Software

• acebayes
• Algorithm 145

Cites Work

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