Bayesian Regression Modeling with INLA is a comprehensive guide for researchers and students who want to learn Bayesian regression analysis using INLA, a powerful computational tool for approximate Bayesian inference. Written by Xiaofeng Wang, this textbook covers both the theoretical foundations of Bayesian regression and practical applications using real-world data sets. The book includes step-by-step instructions for implementing Bayesian regression models in INLA and provides examples of how to interpret and visualize the results.With a focus on applied Bayesian analysis, this book is an essential resource for anyone interested in using INLA to conduct Bayesian regression analysis. Whether you are a student or a researcher in statistics, epidemiology, ecology, or any other field that uses regression analysis, Bayesian Regression Modeling with INLA will provide you with the tools you need to conduct cutting-edge research and analysis.