Best linear estimation via minimization of relative mean squared error

DOI10.1007/S11222-017-9792-0zbMath1430.62161OpenAlexW2770884472MaRDI QIDQ2329747

Lin Su, Howard D. Bondell

Publication date: 18 October 2019

Published in: Statistics and Computing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s11222-017-9792-0

zbMATH Keywords

ridge regressionordinary least squaresbiased linear estimatorsmallest relative mean squared error

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Uses Software

• CVX

Cites Work

• Estimating the dimension of a model
• Graph Implementations for Nonsmooth Convex Programs
• Generalized Cross-Validation as a Method for Choosing a Good Ridge Parameter
• Simultaneous prediction intervals for all distances from the “best”
• Effective degrees of freedom: a flawed metaphor
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• A new look at the statistical model identification
• Unnamed Item

This page was built for publication: Best linear estimation via minimization of relative mean squared error