Estimating a mean matrix: boosting efficiency by multiple affine shrinkage

DOI10.1007/s10463-007-0128-2zbMath1294.62122OpenAlexW2136958045MaRDI QIDQ734400

Rudolf Beran

Publication date: 13 October 2009

Published in: Annals of the Institute of Statistical Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10463-007-0128-2

zbMATH Keywords

regularizationtotal least squaresrank reductionpenalized least squaresEfron-Morris fit

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Generalized linear models (logistic models) (62J12)

Uses Software

• VanHuffel

Cites Work

• An Analysis of the Total Least Squares Problem
• Optimal filtering of square-integrable signals in Gaussian noise
• Estimation in a multivariate errors in variables regression model: Large sample results
• Superefficient estimation of multivariate trend.
• ADAPTIVE ESTIMATORS OF A MEAN MATRIX: TOTAL LEAST SQUARES VERSUS TOTAL SHRINKAGE
• Empirical Bayes on vector observations: An extension of Stein's method
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: Estimating a mean matrix: boosting efficiency by multiple affine shrinkage