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 ...

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 ...

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, ...

A python package for penalized generalized linear models that supports fitting and model selection for structured, adaptive and non-convex penalties.

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

Understanding the General Linear Model is essential for conducting rigorous statistical analyses, making informed inferences about relationships between variables, and developing predictive models.

Abstract Generalized linear models (GLMs) are used in high-dimensional machine learning, statistics, communications, and signal processing. In this paper we analyze GLMs when the data matrix is random ...