Shriknage estimators with general quadratic loss and differentiable or paratially differentiable shrinkage function
DOI10.1080/07362999008809203zbMath0749.62048OpenAlexW2088262981MaRDI QIDQ4712981
Publication date: 25 June 1992
Published in: Stochastic Analysis and Applications (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/07362999008809203
maximum likelihood estimatorshrinkage estimatorsgeneral quadratic losspartial differentiability\(n\)-dimensional normal linear modeldifferentiable shrinkage functionsunbiased estimator of the risk
Estimation in multivariate analysis (62H12) Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)
Cites Work
- Unnamed Item
- Unnamed Item
- Estimation of the mean of a multivariate normal distribution
- Minimax estimators of the mean of a multivariate normal distribution
- Admissible minimax estimation of a multivariate normal mean with arbitrary quadratic loss
- Minimax estimation of a multivariate normal mean under arbitrary quadratic loss
- Proper Bayes minimax estimators of the multivariate normal mean vector for the case of common unknown variances
- A family of admissible minimax estimators of the mean of a multivariate normal distribution
This page was built for publication: Shriknage estimators with general quadratic loss and differentiable or paratially differentiable shrinkage function
