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, ...

If, in addition, a variance function is specified, this leads to a functional estimating equation which corresponds to maximizing a functional quasi-likelihood. This general approach includes the ...

Dominik Rothenhäusler, Peter Bühlmann, Nicolai Meinshausen, CAUSAL DANTZIG, The Annals of Statistics, Vol. 47, No. 3 (June 2019), pp. 1688-1722 ...

Parametric versus Semi/nonparametric Regression Models Course Topics Linear models, generalized linear models, and nonlinear models are examples of parametric regression models because we know the ...

Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals. Model choice, fitting and validation.