This course provides an introduction to the mathematical treatment of the theory of statistical inference using the concept of likelihood as a unifying theme.
Regression modelling is a basic tool of statistics, because it describes how a random variable of interest may depend on other variables. The aim of this course is to familiarize students with the basis of regression modelling, and of some related topics.
This course is intended to give a brief overview of how to prove consistency results in nonparametric regression. In particular, we will focus on least-square regression estimators. Some connections to the empirical risk minimization (ERM) problem will be discussed from time to time.