X ij = [x ij1, ... , x ijp]' The Generalized Estimating Equation of Liang and Zeger (1986) for estimating the p ×1 vector of regression parameters is an extension of the independence estimating ...

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 ...

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, ...

Data analysis of Air BnB data in Barcelona and London using a subset of data investigated by Gyódi, K., & Nawaro, Ł. Generalised Linear Models have been fitted to examine weekend price differences and ...

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

GAM is a model which allows the linear model to learn nonlinear relationships. it can be considered as an extension of linear model.