A Note on a Commonly Used Ridge Regression Monte Carlo Design

DOI10.1080/03610926.2013.775299zbMath1329.62325OpenAlexW2128056193MaRDI QIDQ3462359

H. E. T. Holgersson

Publication date: 5 January 2016

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

Full work available at URL: https://doi.org/10.1080/03610926.2013.775299

zbMATH Keywords

Monte Carlo simulationridge regressionmulticollinearitydesign matrixexcess mean square error

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Monte Carlo methods (65C05)

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Cites Work

• Should stochastic or non-stochastic exogenous variables be used in Monte Carlo experiments?
• A simulation study on SPSS ridge regression and ordinary least squares regression procedures for multicollinearity data
• On necessary and sufficient condition for superiority of ridge estimator over least squares estimator
• Choosing Ridge Parameter for Regression Problems
• Performance of Some New Ridge Regression Estimators
• Confidence intervals in ridge regression by bootstrapping the dependent variable: a simulation study
• Linear Statistical Inference and its Applications