Solving Autocorrelation Problems in General Linear Model on a Real-World Application

Delving into one of the most common nightmares for data scientists

Introduction

One of the biggest problems in linear regression is autocorrelated residuals. In this context, this article revisits linear regression, delves into the Cochrane–Orcutt procedure as a way to solve this problem, and explores a real-world application in fMRI brain activation analysis.

General Linear Model (GLM) revisited

Linear regression is probably one of the most important tools for any data scientist. However, …

correlation fmri linear regression time-series-analysis