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Posterior Consistency of Bayesian Inverse Regression and Inverse Reference Distributions

1 May 2020
D. Chatterjee
S. Bhattacharya
ArXiv (abs)PDFHTML
Abstract

We consider Bayesian inference in inverse regression problems where the objective is to infer about unobserved covariates from observed responses and covariates. We establish posterior consistency of such unobserved covariates in Bayesian inverse regression problemsunder appropriate priors in a leave-one-out cross-validation setup. We relate this to posterior consistency of inverse reference distributions (Bhattacharya (2013)) for assessing model adequacy. We illustrate our theory and methods with various examples of Bayesian inverse regression, along with adequate simulation experiments.

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