Mathematics
4 years ago

Highly correlated variables in regression models lead to inaccurate predictions.

Pure and applied mathematics
ILL-CONDITIONING IN LINEAR REGRESSION MODELS AND ITS DIAGNOSTICS
Hamid Ghorbani

Paper Summary

Related papers

Theme background image
Mathematics
8 years ago

New study reveals best method to solve regression analysis multicollinearity problem.

Multicollinearity
1 view
Theme background image
Mathematics
3 years ago

New method simplifies regression analysis for highly correlated predictor variables.

Multicollinearity
Chemometrics
Regularization Methods
1 view
Theme background image
Environmental Science
3 years ago

Multicollinearity in PLS1 Modeling Leads to Unexplainable Results.

Wastewater Monitoring
Intelligent Control

Multicollinearity, when variables in a linear regression model are highly correlated, can cause issues with parameter estimates and model interpretation. This study reviews the problem, discusses ways to detect multicollinearity, and emphasizes the importance of eigenvalues and eigenvectors in identifying it. The researchers then applied these methods to a real dataset to diagnose multicollinearity in a linear regression model.