• Corpus ID: 220525800

A Bayesian Multiple Testing Paradigm for Model Selection in Inverse Regression Problems

  title={A Bayesian Multiple Testing Paradigm for Model Selection in Inverse Regression Problems},
  author={Debashis Chatterjee and Sourabh Bhattacharya},
  journal={arXiv: Statistics Theory},
In this article, we propose a novel Bayesian multiple testing formulation for model and variable selection in inverse setups, judiciously embedding the idea of inverse reference distributions proposed by Bhattacharya (2013) in a mixture framework consisting of the competing models. We develop the theory and methods in the general context encompassing parametric and nonparametric competing models, dependent data, as well as misspecifications. Our investigation shows that asymptotically the… 
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