The principal problem with principal components regression

DOI10.1080/25742558.2019.1622190zbMath1428.62255OpenAlexW2947314935MaRDI QIDQ5203802

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Publication date: 9 December 2019

Published in: Cogent Mathematics & Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/25742558.2019.1622190

zbMATH Keywords

data reductionfactor analysisbig dataPCRprincipal components regression

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (3)

Principal component regression in GAMLSS applied to Greek–German government bond yield spreads ⋮ Confronting collinearity in environmental regression models: evidence from world data ⋮ Comparing six shrinkage estimators with large sample theory and asymptotically optimal prediction intervals

Uses Software

• Eigenstrat

Cites Work

• Surrogate models in ill-conditioned systems
• On the number of principal components: a test of dimensionality based on measurements of similarity between matrices
• Searching for the core variables in principal components analysis
• Principal component analysis: a review and recent developments
• Statistical learning and selective inference
• A Biometrics Invited Paper. The Analysis and Selection of Variables in Linear Regression
• Forecasting Using Principal Components From a Large Number of Predictors
• RELATIONS BETWEEN TWO SETS OF VARIATES

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