In this module, we will introduce generalized linear models (GLMs) through the study of binomial data. In particular, we will motivate the need for GLMs; introduce the binomial regression model, ...

Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, modeling the state damaged/not damaged of cells after treated with ...

The generalized least squares estimator (GLSE) and the feasible generalized least squares estimator (FGLSE) are, separately, extended to the generalized and the ...

Troy Segal is an editor and writer. She has 20+ years of experience covering personal finance, wealth management, and business news. Eric's career includes extensive work in both public and corporate ...

The generalized linear model (Nelder & Wedderburn, 1972) has become an elegant and practical option to classical least-squares linear model building. We consider the specific problem of generalized ...

Will Kenton is an expert on the economy and investing laws and regulations. He previously held senior editorial roles at Investopedia and Kapitall Wire and holds a MA in Economics from The New School ...