Number of predictors and multicollinearity: What are their effects on error and bias in regression?

DOI10.1080/03610918.2017.1371750OpenAlexW2751597636MaRDI QIDQ5086132

Parul Acharya, Li Hua Xu, Stephen A. Sivo, Matthew Ryan Lavery

Publication date: 1 July 2022

Published in: Communications in Statistics - Simulation and Computation (Search for Journal in Brave)

Full work available at URL: https://scholarworks.bgsu.edu/cgi/viewcontent.cgi?article=1013&context=seflp_pubs

zbMATH Keywords

statistical methodsmulticollinearitymultiple regressionMonte Carlo simulation study

Mathematics Subject Classification ID

Statistics (62-XX)

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A modelling framework for regression with collinearity ⋮ Robust correlation scaled principal component regression

Cites Work

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