Near-collinearity in linear regression revisited: The numerical vs. the statistical perspective

DOI10.1080/03610926.2018.1513147OpenAlexW2901487316WikidataQ128990666 ScholiaQ128990666MaRDI QIDQ5077915

Aris Spanos

Publication date: 20 May 2022

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2018.1513147

zbMATH Keywords

ill-conditioningstatistical misspecificationvariance inflation factorscentering datanear-collinearitynorm condition numbertrend polynomialsvariance singular value decomposition

Mathematics Subject Classification ID

Statistics (62-XX)

Cites Work

• Collinearity and least squares regression
• How bad are Hankel matrices?
• The problem of near-multicollinearity revisited: erratic vs systematic volatility.
• Probability with Martingales
• Ridge Regression in Practice
• Correlation in Polynomial Regression
• On normality and the linear regression model
• Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
• On Simpson's Paradox and the Sure-Thing Principle
• All of Nonparametric Statistics
• Numerical Methods of Statistics
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