Multiple regression and regression diagnostics. Generalised linear models; the exponential family, the linear predictor, link functions, analysis of deviance, parameter estimation, deviance residuals.

Generalized Linear Models Generalized Linear Models Course Topics Many response variables are handled poorly by regression models when the errors are assumed to be normally distributed. For example, ...

In this article, we obtain an estimator of the regression parameters for generalized linear models, using the Jacobian technique. We restrict ourselves to the natural exponential family for the ...

Course Topics"Generalized Linear Models," Tuesday, April 6: The third LISA mini course for the 2010 Spring semester focuses on appropriate model building using generalized linear models. While ...

Topics include: general theory of regression and generalised linear models, linear regression, logistic regression for binary data, models for ordered and unordered (nominal) responses, log-linear ...

In generalized linear models, the response is assumed to possess a probability distribution of the exponential form. That is, the probability density of the response Y for continuous response ...

A generalized linear model extends the traditional linear model and is, therefore, applicable to a wider range of data analysis problems. A generalized linear model consists of the following ...

We give examples of the Poisson-gamma, binomial-beta and gamma-inverse gamma hierarchical generalized linear models. A resolution is proposed for the apparent difference between population-averaged ...

Generalized linear mixed model We use a binomial trait as an example to demonstrate the new methodology, although the method can be applied to other discrete traits. Let yj be the number of events ...