Lecture

Generalized Linear Models: GLMs for Non-Gaussian Data

Description

This lecture by the instructor covers Generalized Linear Models (GLMs) for non-Gaussian data, focusing on GLMs for regression with exponential family responses. The lecture delves into the interpretation of the natural link function, the asymptotic normality of the Maximum Likelihood Estimator (MLE) in GLMs, and measures of fit using deviance. It also discusses residuals, leverage, and the Cook statistic, providing insights into logistic regression for binary data and loglinear regression for count data. The lecture concludes with remarks on the scale parameter in GLMs.

About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.