Acknowledgments

I began developing our graphical user interface (GUI) in 2016, after being diagnosed with cervical dystonia. I worked on this side project during weekends, which I called ``nerd weekends,’’ and it served as a form of release from my health condition. Once I began to recover, I invited Mateo Graciano, my former student, business partner, and friend, to join the project. He has been instrumental in developing our GUI, and I am enormously grateful to him.

I would also like to thank the members of the BEsmarter research group at Universidad EAFIT, as well as the NUMBATs members at Monash University, for their valuable feedback and recommendations to improve our GUI.

This book is an extension of the paper (Ramírez-Hassan and Graciano-Londoño 2020), which serves as a brief user guide for our GUI. I decided to write this book to explain the underlying theory and code in our GUI, and to use it as a textbook in my course on Bayesian econometrics/statistics. I am grateful to my students in this course; their insights and thoughtful questions have deepened my understanding of the material.

I would like to thank Chris Parmeter for his valuable suggestions on how to present our user guide; Professors Raúl Pericchi and Juan Carlos Correa for introducing me to Bayesian statistics; and Liana Jacobi, Tomasz Wozniak, and Chun Fung Kwok (Jackson) from the University of Melbourne, as well as David Frazier from Monash University, for their engaging discussions and fruitful collaborations in Bayesian econometrics and statistics. I am also deeply grateful to Professor Peter Diggle for his unwavering support of my career, and especially to Professor Gael Martin, who gave me the opportunity to work with her and has been a constant source of intellectual inspiration.

I also wish to acknowledge my colleagues and staff at Universidad EAFIT for their continuous support.

Finally, I acknowledge the use of ChatGPT, which assisted me in improving the grammar, clarity, and flow of the text, as well as in tidying up some of the code presented in this book. Nevertheless, all concepts, mathematical developments, and underlying logic are entirely my own, based on my understanding and readings of the literature. Any remaining errors are solely my responsibility, for which I apologize in advance. I sincerely thank the reader and hope that this book proves useful.

To my parents, Orlando and Nancy, who have always been there for me with their unconditional support. They have taught me that the primary aspect of human spiritual evolution is humility, a lesson I am still learning every day. To my wife, Estephania, for her unwavering love and support.

References

Ramírez-Hassan, A., and M. Graciano-Londoño. 2020. “A GUIded Tour of Bayesian Regression.” The R Journal 13 (2): 135–52.