Shrinkage structure in biased regression

DOI10.1016/j.jmva.2006.06.011zbMath1133.62051OpenAlexW2100634825MaRDI QIDQ151044

Alain Mom, Pierre Druilhet, Alain Mom, Pierre Druilhet

Publication date: February 2008

Published in: Journal of Multivariate Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jmva.2006.06.011

zbMATH Keywords

James-Stein estimatorsignal-to-noise ratiobiased regressionregression on componentsshrinkage factors

Mathematics Subject Classification ID

Factor analysis and principal components; correspondence analysis (62H25) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (6)

Maximum Likelihood Estimators in a Two Step Model for PLS ⋮ Characterization of estimators uniformly shrinking on subspaces ⋮ New shrinkage-type estimators in a linear regression model when multicollinearity is severe ⋮ Adjustive Liu-Type Estimators in Linear Regression Models ⋮ Improved Liu estimator in a linear regression model ⋮ liureg

Cites Work

• Partial least squares algorithm yields shrinkage estimators
• PLS regression: a directional signal-to-noise ratio approach
• Shrinkage Structure of Partial Least Squares
• On the structure of partial least squares regression
• The Peculiar Shrinkage Properties of Partial Least Squares Regression
• A Statistical View of Some Chemometrics Regression Tools
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