# Bayes model selection

@article{Han2017BayesMS, title={Bayes model selection}, author={Qiyang Han}, journal={arXiv: Statistics Theory}, year={2017} }

We offer a general Bayes theoretic framework to tackle the model selection problem under a two-step prior design: the first-step prior serves to assess the model selection uncertainty, and the second-step prior quantifies the prior belief on the strength of the signals within the model chosen from the first step.
We establish non-asymptotic oracle posterior contraction rates under (i) a new Bernstein-inequality condition on the log likelihood ratio of the statistical experiment, (ii) a local… Expand

#### 5 Citations

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