Lecture

Linear Regression: Absence or Presence of Covariates

Description

This lecture covers the fundamental concepts of linear regression, focusing on the absence or presence of covariates. It explains the distinction between marginal inference and regression, where observations are generated under different experimental conditions. The lecture delves into the bewildering variety of models that can be captured by the general specification of independent distributions. It also discusses the tools of the trade, starting from Gaussian linear regression and gradually generalizing to subspaces, projection matrices, and optimal dimension reduction. The concept of subspaces and spectra associated with real matrices is explored, along with orthogonal projections and the singular value decomposition theorem.

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.