Duration: 12h. 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 ...

You construct a generalized linear model by deciding on response and explanatory variables for your data and choosing an appropriate link function and response probability distribution. Some examples ...

What is a Generalized Linear Model? A traditional linear model is of the form where y i is the response variable for the i th observation. The quantity x i is a column vector of covariates, or ...

Course TopicsLinear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the function that describes the relationship between the ...

N. E. Breslow, D. G. Clayton, Approximate Inference in Generalized Linear Mixed Models, Journal of the American Statistical ... are assumed to be conditionally independent with means that depend on ...

Joel L. Horowitz, Enno Mammen, Rate-Optimal Estimation for a General Class of Nonparametric Regression Models with Unknown Link Functions, The Annals of Statistics, Vol. 35, No. 6 (Dec., 2007), pp.