These notes cover the second semester in a two-semester sequence on statistical modeling. It focuses on constructing, drawing conclusions from, and critiquing probabilistic models. Planned topics include generalized linear models, the bootstrap, hierarchichal models, nonparametric estimation, and generalized estimating equations. [...] In this collection of notes, we briefly outline the main thrust of this course by discussing (at a high level of generality) the topic of probabilistic modeling. Throughout this course we will focus on the application of probabilistic modeling with an eye ... Read more →

A Short Course on Nonparametric Curve Estimation. MSc in Applied Mathematics. EAFIT University (Colombia). [...] This course is intended to provide an introduction to nonparametric estimation of the density and regression functions from, mostly, the perspective of kernel smoothing. The emphasis is placed in building intuition behind the methods, gaining insights into their asymptotic properties, and showing their application through the use of statistical software. The software employed in the course is the statistical language R and its most common IDE (Integrated Development ... Read more →