Robust Approximate Bayesian Inference With Synthetic Likelihood
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Publication:5066481
DOI10.1080/10618600.2021.1875839OpenAlexW3123825128MaRDI QIDQ5066481
Christopher C. Drovandi, David T. Frazier
Publication date: 29 March 2022
Published in: Journal of Computational and Graphical Statistics (Search for Journal in Brave)
Full work available at URL: https://arxiv.org/abs/1904.04551
approximate Bayesian computationmodel misspecificationslice samplinglikelihood-free inferencerobust Bayesian inferencesynthetic likelihood
Related Items (8)
A comparison of likelihood-free methods with and without summary statistics ⋮ Efficient Bayesian Synthetic Likelihood With Whitening Transformations ⋮ Metropolis–Hastings via Classification ⋮ Modularized Bayesian analyses and cutting feedback in likelihood-free inference ⋮ Bayesian Inference Using Synthetic Likelihood: Asymptotics and Adjustments ⋮ Some models are useful, but how do we know which ones? Towards a unified Bayesian model taxonomy ⋮ Detecting conflicting summary statistics in likelihood-free inference ⋮ Summary statistics and discrepancy measures for approximate Bayesian computation via surrogate posteriors
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