Correlated Component Regression: Re-thinking Regression in the Presence of Near Collinearity

DOI10.1007/978-1-4614-8283-3_3zbMath1428.62254OpenAlexW180615875MaRDI QIDQ4973039

Jay Magidson

Publication date: 2 December 2019

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

Full work available at URL: https://doi.org/10.1007/978-1-4614-8283-3_3

zbMATH Keywords

cross-validationscale invariancevariable selectionmulticollinearitybig datahigh dimensional dataPLS regressionsuppressor variablecorrelated component regression

Mathematics Subject Classification ID

Measures of association (correlation, canonical correlation, etc.) (62H20) Generalized linear models (logistic models) (62J12) Analysis of variance and covariance (ANOVA) (62J10)

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Uses Software

• ppls

Cites Work

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• Some theory for Fisher's linear discriminant function, `naive Bayes', and some alternatives when there are many more variables than observations
• Sparse partial least squares classification for high dimensional data
• Covariance Analysis of Censored Survival Data Using Log-Linear Analysis Techniques
• Bayesian Wavelet Regression on Curves With Application to a Spectroscopic Calibration Problem
• Sparse Partial Least Squares Regression for Simultaneous Dimension Reduction and Variable Selection

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