The EM algorithm is often used for finding the maximum likelihood estimates in generalized linear models with incomplete data. In this article, the author presents a robust method in the framework of ...
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 ...
Proceedings of the Royal Society of London. Series A, Mathematical and Physical Sciences, Vol. 275, No. 1361 (Sep. 24, 1963), pp. 175-189 (15 pages) This paper is a sequel to an earlier one by ...
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, ...
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 ...
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