[edited Nov 30, 2020] The purpose of this post is to demonstrate the advantages of the Student’s \(t\)-distribution for regression with outliers, particularly within a Bayesian framework. I make assumptions I’m presuming you are familiar with linear regression, familiar with the basic differences between frequentist and Bayesian approaches to fitting regression models, and have a sense that the issue of outlier values is a pickle worth contending with. All code in is R, with a heavy use o...
