Near-collinearity in linear regression revisited: The numerical vs. the statistical perspective
From MaRDI portal
Publication:5077915
DOI10.1080/03610926.2018.1513147OpenAlexW2901487316WikidataQ128990666 ScholiaQ128990666MaRDI QIDQ5077915
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
ill-conditioningstatistical misspecificationvariance inflation factorscentering datanear-collinearitynorm condition numbertrend polynomialsvariance singular value decomposition
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
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
This page was built for publication: Near-collinearity in linear regression revisited: The numerical vs. the statistical perspective