Collinearity: revisiting the variance inflation factor in ridge regression

DOI10.1080/02664763.2014.980789OpenAlexW2020605840MaRDI QIDQ5130183

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Publication date: 4 November 2020

Published in: Journal of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/02664763.2014.980789

zbMATH Keywords

covariance matrixridge regressionlinear regressioncollinearityvariance inflation factor

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (13)

Designs enhancing Fisher information ⋮ On a generalization of the test of endogeneity in a two stage least squares estimation ⋮ The red indicator and corrected VIFs in generalized linear models ⋮ A note about the corrected VIF ⋮ Standardization of Variables and Collinearity Diagnostic in Ridge Regression ⋮ Choice of the ridge factor from the correlation matrix determinant ⋮ Bayesian ridge regression for survival data based on a vine copula-based prior ⋮ A Bayesian asymmetric logistic model of factors underlying team success in top‐level basketball in Spain ⋮ Collinearity diagnostic applied in ridge estimation through the variance inflation factor ⋮ A new multicollinearity diagnostic for generalized linear models ⋮ Partial ridge regression under multicollinearity ⋮ Mitigating collinearity in linear regression models using ridge, surrogate and raised estimators ⋮ Confronting collinearity in environmental regression models: evidence from world data

Cites Work

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• Surrogate models in ill-conditioned systems
• Revision: variance inflation in regression
• The corrected VIF (CVIF)
• Anomalies in the Foundations of Ridge Regression
• A simulation study on SPSS ridge regression and ordinary least squares regression procedures for multicollinearity data
• Ridge Regression in Practice
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Ridge Regression: Applications to Nonorthogonal Problems
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation

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