ABSTRACT
This chapter describes the notion of a statistical model with a focus on the notion of a smooth and stable dominated parametric model. The likelihood function, score function, information function, Fisher information, and quadratic score are introduced for such models. Important identities are established for these quantities as well as their properties under smooth reparametrization. The developments are illustrated through numerous examples that will reappear from time to time in the remaining parts of the book.
