Regularized linear and kernel redundancy analysis

DOI10.1016/j.csda.2007.02.014zbMath1452.62421OpenAlexW2165507622MaRDI QIDQ1020827

Yoshio Takane, Heungsun Hwang

Publication date: 2 June 2009

Published in: Computational Statistics and Data Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.csda.2007.02.014

zbMATH Keywords

bootstrap methodpermutation testsridge regressionkernel methodsGaussian kernelgeneralized singular value decomposition (GSVD)\(J\)-fold cross validationreduced rank approximation

Mathematics Subject Classification ID

Computational methods for problems pertaining to statistics (62-08) Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items

Kernel generalized canonical correlation analysis, Robust approaches to redundancy analysis, Regularized reduced rank growth curve models, Regularized fuzzy clusterwise ridge regression, Regularized nonsymmetric correspondence analysis, Regularized generalized canonical correlation analysis, Optimal selection of reduced rank estimators of high-dimensional matrices, Regularized partial and/or constrained redundancy analysis, Regularized multiple-set canonical correlation analysis, Editorial: Statistical learning methods including dimensionality reduction, Continuum redundancy-\textit{PLS} regression: a simple continuum approach, Regularized generalized structured component analysis

Uses Software

• fda (R)
• sedaR
• ElemStatLearn
• Canoco

Cites Work

• Regularized partial and/or constrained redundancy analysis
• Redundancy analysis: an alternative for canonical correlation analysis
• Multivariate reduced-rank regression
• Linear regression.
• Principal component analysis with external information on both subjects and variables
• On ridge operators
• Functional data analysis.
• On multivariate ridge regression
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Estimating Linear Restrictions on Regression Coefficients for Multivariate Normal Distributions
• The elements of statistical learning. Data mining, inference, and prediction
• Constrained principal component analysis: A comprehensive theory
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