Corpus ID: 220871712

Robust Inference and Model Criticism Using Bagged Posteriors

@article{Huggins2019RobustIA,
  title={Robust Inference and Model Criticism Using Bagged Posteriors},
  author={J. Huggins and J. W. Miller},
  journal={arXiv: Methodology},
  year={2019}
}
  • J. Huggins, J. W. Miller
  • Published 2019
  • Computer Science, Mathematics
  • arXiv: Methodology
  • Standard Bayesian inference is known to be sensitive to model misspecification, leading to unreliable uncertainty quantification and poor predictive performance. However, finding generally applicable and computationally feasible methods for robust Bayesian inference under misspecification has proven to be a difficult challenge. An intriguing, easy-to-use, and widely applicable approach is to use bagging on the Bayesian posterior ("BayesBag"); that is, to use the average of posterior… CONTINUE READING
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