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3. Selection of regression variables
In this section, we focus on Bayesian variable selection in Gaussian linear regression. We cover many aspects in order to provide the reader with a precise guide and demonstrate the applicability of the Bayesian approach in a concrete context. We successively study two cases where a priori laws on model parameters are respectively informative and non-informative.
3.1 Introduction
Bayesian variable selection in linear regression has been extensively studied, providing a fertile field of experimentation for the comparison of a priori laws and decision procedures. Among others, we can cite the following references
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Selection of regression variables
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