ABSTRACT
A master chef becomes a master chef by mastering the basic elements of cooking, from flavor to texture to smell. When cooking then, they can combine these elements without relying on rigid step-by-step cookbook directions. Similarly, in building statistical models, Bayesian or frequentist, there is no rule book to follow. Rather, it's important to familiarize ourselves with some basic modeling building blocks and develop the ability to use these in different combinations to suit the task at hand. With this, in Chapter 18 you will practice cooking up new models from the ingredients you already have. To focus on the new concepts in this chapter, we'll utilize weakly informative priors throughout. Please review Chapters 12 and 13 for a refresher on tuning prior models in the Poisson and logistic regression settings, respectively. The same ideas apply here.
