Collinearity diagnostic applied in ridge estimation through the variance inflation factor

DOI10.1080/02664763.2015.1120712OpenAlexW2292939562MaRDI QIDQ5138125

Román Salmerón-Gómez, María del Mar López Martín, Catalina García-García, José García Pérez

Publication date: 3 December 2020

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

Full work available at URL: https://doi.org/10.1080/02664763.2015.1120712

zbMATH Keywords

ridge regressionmultiple linear regressioncollinearitymultivariables

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (8)

Designs enhancing Fisher information ⋮ An unequal adjacent grey forecasting air pollution urban model ⋮ Variance Inflation Factor and Condition Number in multiple linear regression ⋮ The red indicator and corrected VIFs in generalized linear models ⋮ Choice of the ridge factor from the correlation matrix determinant ⋮ MCVIS: A New Framework for Collinearity Discovery, Diagnostic, and Visualization ⋮ Confronting collinearity in environmental regression models: evidence from world data ⋮ Residualization: justification, properties and application

Uses Software

• R

Cites Work

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• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Ridge Regression: Applications to Nonorthogonal Problems
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
• A method for the solution of certain non-linear problems in least squares
• Standardization of Variables and Collinearity Diagnostic in Ridge Regression

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