Model choice problems using approximate Bayesian computation with applications to pathogen transmission data sets

DOI10.1111/biom.12249zbMath1419.62388OpenAlexW1937055226WikidataQ35320434 ScholiaQ35320434MaRDI QIDQ3465747

Christopher C. Drovandi, Xing Ju Lee, Anthony N. Pettitt

Publication date: 22 January 2016

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/biom.12249

zbMATH Keywords

approximate Bayesian computationmodel choiceMRSAHagelloch measlesTristan da Cunha cold outbreak

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Bayesian inference (62F15)

Related Items (4)

Optimal Bayesian design for discriminating between models with intractable likelihoods in epidemiology ⋮ Exact and approximate Bayesian inference for low integer-valued time series models with intractable likelihoods ⋮ Alive SMC²: Bayesian model selection for low‐count time series models with intractable likelihoods ⋮ ABC model selection for spatial extremes models applied to south Australian maximum temperature data

Cites Work

• Unnamed Item
• Unnamed Item
• Reversible jump Markov chain Monte Carlo computation and Bayesian model determination
• The pseudo-marginal approach for efficient Monte Carlo computations
• Sequential Monte Carlo on large binary sampling spaces
• Estimating the dimension of a model
• A modified score function estimator for multinomial logistic regression in small samples.
• Simulation-based Bayesian inference for epidemic models
• Likelihood-free estimation of model evidence
• Inference for Epidemics with Three Levels of Mixing: Methodology and Application to a Measles Outbreak
• Estimation of Parameters for Macroparasite Population Evolution Using Approximate Bayesian Computation
• Multinomial logit bias reduction via the Poisson log-linear model
• Semi-automatic selection of summary statistics for ABC model choice
• Multivariate Markov Process Models for the Transmission of Methicillin‐Resistant Staphylococcus Aureus in a Hospital Ward
• Marginal Likelihood Estimation via Power Posteriors
• Adaptive approximate Bayesian computation
• A Network‐based Analysis of the 1861 Hagelloch Measles Data
• Bayesian Measures of Model Complexity and Fit
• Bias reduction of maximum likelihood estimates
• Statistical inference and model selection for the 1861 Hagelloch measles epidemic
• ABC likelihood-free methods for model choice in Gibbs random fields
• Bayesian analysis for emerging infectious diseases

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