I started our GUI in the 2016 after being diagnosticed with cervical dystonia. I used to work in this side project on weekends, I named this time “nerd weekends,” and it was a kind of release from my health condition. Once I got better, I invited Mateo Graciano, my former student, business partner and friend, to be part of the project, he helped me a lot developing our GUI, and I am enormously thankful to Mateo. I would also like to thank members of the BEsmarter research group from Universidad EAFIT, and NUMBATs members from Monash University for your comments and recomendations to improve our GUI.

This book is an extension of the paper A GUIded tour of Bayesian regression (Ramírez-Hassan and Graciano-Londoño 2020), which is a brief user guide of our GUI. So, I decided to write this book to show the underlying theory and codes in our GUI, and use it as a text book in my course in Bayesian econometrics. I acknowledge and offer my gratitude to my students in this subject, their insight and thoughtful questions have helped me to get a better understanding of this material.

I also thank Chris Parmeter for your suggestions about how to present our user guide, Professor Raul Pericchi and Juan Carlos Correa who introduced me to Bayesian statistics, Liana Jacobi and Chun Fung Kwok (Jackson) from the University of Melbourne and David Frazier from Monash University for nice talks and amazing colaborations in Bayesian Econometrics, Professor Peter Diggle to support my career, and particularly, Professor Gael Martin, who gave me a chance to work with her, she is an inspiring intellectual figure. Finally, my colleagues and staff from Universidad EAFIT have always given me their support.

To my parents, Orlando and Nancy, who have given me their unconditional support. They have taught me that the primary aspect of the human being’s spiritual evolution is humility. Unfortunately, I have not learned very well their lesson, yet.


Ramírez-Hassan, A., and M. Graciano-Londoño. 2020. “A GUIded Tour of Bayesian Regression.” Universidad EAFIT.