Variational Bayesian inference for linear and logistic regression
This is an incremental contribution for researchers and practitioners needing accessible tools for Bayesian inference in regression models.
The article tackles the problem of implementing variational Bayesian inference for linear and logistic regression, including automatic relevance determination, by providing a tutorial and MATLAB/Octave functions, with the result being freely available code for practical use.
The article describe the model, derivation, and implementation of variational Bayesian inference for linear and logistic regression, both with and without automatic relevance determination. It has the dual function of acting as a tutorial for the derivation of variational Bayesian inference for simple models, as well as documenting, and providing brief examples for the MATLAB/Octave functions that implement this inference. These functions are freely available online.