Choice of the ridge factor from the correlation matrix determinant
From MaRDI portal
Publication:5107320
DOI10.1080/00949655.2018.1543423OpenAlexW2899855318WikidataQ128998135 ScholiaQ128998135MaRDI QIDQ5107320
Román Salmerón-Gómez, Claudia I. Garcia, Catalina B. García
Publication date: 27 April 2020
Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00949655.2018.1543423
Related Items (2)
Confronting collinearity in environmental regression models: evidence from world data ⋮ Residualization: justification, properties and application
Cites Work
- Unnamed Item
- Unnamed Item
- On the almost unbiased ridge regression estimator
- On Some Ridge Regression Estimators: An Empirical Comparisons
- Condition Numbers and Minimax Ridge Regression Estimators
- A Simulation Study of Some Ridge Estimators
- Ridge regression:some simulations
- A Monte Carlo Evaluation of Some Ridge-Type Estimators
- A simulation study of ridge and other regression estimators
- A Class of Biased Estimators in Linear Regression
- Tests of regression coefficients under ridge regression models
- Choosing Ridge Parameter for Regression Problems
- Performance of Some New Ridge Regression Estimators
- Variance Inflation Factor and Condition Number in multiple linear regression
- Collinearity: revisiting the variance inflation factor in ridge regression
- Collinearity diagnostic applied in ridge estimation through the variance inflation factor
- Ridge Regression: Biased Estimation for Nonorthogonal Problems
- Ridge Regression: Applications to Nonorthogonal Problems
- Generalized Inverses, Ridge Regression, Biased Linear Estimation, and Nonlinear Estimation
- Standardization of Variables and Collinearity Diagnostic in Ridge Regression
This page was built for publication: Choice of the ridge factor from the correlation matrix determinant
