Regression methods for high dimensional multicollinear data

DOI10.1080/03610910008813652zbMath1008.62503OpenAlexW2021610169MaRDI QIDQ4787632

Lorna S. Aucott, James Currall, Paul H. Garthwaite

Publication date: 2000

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

Full work available at URL: https://doi.org/10.1080/03610910008813652

zbMATH Keywords

partial least squaresdata reductionhigh-dimensional datastepwise regressionbiased regressionprincipal components regressionlatent root regressionnear infrared spectra

Mathematics Subject Classification ID

Related Items (5)

APPLIED REGRESSION ANALYSIS BIBLIOGRAPHY UPDATE 2000–2001 ⋮ Principal component estimation of functional logistic regression: discussion of two different approaches ⋮ Using principal components for estimating logistic regression with high-dimensional multicollinear data ⋮ Discussion of different logistic models with functional data. Application to systemic lupus erythematosus ⋮ Variable Selection Methods in High-dimensional Regression—A Simulation Study

Cites Work

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• Principal component analysis.
• On the structure of partial least squares regression
• An Interpretation of Partial Least Squares
• A Statistical View of Some Chemometrics Regression Tools

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