About this document
Regression GLM by saarishtk is a document available to read on EtoBox.
The document provides an overview of Generalized Linear Models (GLMs), which extend ordinary linear regression to accommodate non-normal response variables through a link function. It includes theoretical foundations, examples of binary and multinomial logistic regression, and data demonstrations using R code. Key components discussed include the exponential family of distributions, likelihood functions, and estimation methods such as Maximum Likelihood Estimation (MLE).
- Author
- saarishtk
- Language
- EN