The linear minimax estimator of stochastic regression coefficients and parameters under quadrat\-ic loss function

DOI10.1016/J.SPL.2006.05.011zbMath1106.62009OpenAlexW2015043905MaRDI QIDQ870319

Sheng-Hua Yu

Publication date: 12 March 2007

Published in: Statistics \& Probability Letters (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.spl.2006.05.011

zbMATH Keywords

random effectslinear modelsmaximum risk function

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05) Minimax procedures in statistical decision theory (62C20)

Related Items (6)

D-optimal designs for linear mixed model with random effects of Dirichlet process ⋮ Matrix linear minimax estimators in a general multivariate linear model under a balanced loss function ⋮ \(R\)-optimal designs in random coefficient regression models ⋮ Minimax estimator of regression coefficient in normal distribution under balanced loss function ⋮ Linear minimax prediction of finite population regression coefficient under a balanced loss function ⋮ Optimal Designs for Random Coefficient Regression Models with Heteroscedastic Errors

Cites Work

• Families of minimax estimators of the mean of a multivariate normal distribution
• Extension of the Gauss-Markov theorem to include the estimation of random effects
• A family of admissible minimax estimators of the mean of a multivariate normal distribution
• A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item

This page was built for publication: The linear minimax estimator of stochastic regression coefficients and parameters under quadrat\-ic loss function