Regression Models […] These notes contain both the theory and practice for the statistical models presented in the course. Regression Analysis is the most common statistical modeling approach used in data analysis, and it is the basis for more advanced statistical and machine learning modeling. In this course, you will received the foundation knowledge in the use of widely used tools in regression analysis. You will learn the basics of regression analysis such as linear regression, logistic regression, Poisson regression, generalized linear regression and generalized additive models. … Read more →

An introduction to generalized additive models (GAMs) is provided, with an emphasis on generalization from familiar linear models. It makes extensive use of the mgcv package in R. Discussion includes common approaches, standard extensions, and relations to other techniques. More technical modeling details are described and demonstrated as well. […] Michael Clark m-clark.github.io … Read more →