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 ...

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 ...

Discover the fundamentals of linear regression and its applications. Learn more and enhance your data analysis skills today.

General Linear Model methods are the most widely used in data analysis in applied empirical research. Still, there exists no compact text that can be used in statistics courses and as a guide in data ...

Linear and logistic regression models are essential tools for quantifying the relationship between outcomes and exposures. Understanding the mathematics behind these models and being able to apply ...

In previous years we have been able to provide places for all students that apply but that may not continue to be the case. An introduction to the theory and application of generalised linear models ...

Engineering is all about choosing the best compromise—both for a SPICE model that provides reasonable fidelity and for the ...