Estimating random effects via adjustment for density maximization

DOI10.1214/10-STS349zbMath1246.62025arXiv1108.3234OpenAlexW2027340191MaRDI QIDQ449828

Ruoxi Tang, Carl N. Morris

Publication date: 1 September 2012

Published in: Statistical Science (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1108.3234

zbMATH Keywords

shrinkageobjective BayesADMStein estimationnormal multilevel model

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Point estimation (62F10) Bayesian inference (62F15)

Related Items (10)

Shrinkage estimation in multilevel normal models ⋮ Empirical Bayes Confidence Intervals for Selected Parameters in High-Dimensional Data ⋮ Estimating variance of random effects to solve multiple problems simultaneously ⋮ A new adjusted maximum likelihood method for the Fay-Herriot small area model ⋮ Multi-Goal Prior Selection: A Way to Reconcile Bayesian and Classical Approaches for Random Effects Models ⋮ A second-order efficient empirical Bayes confidence interval ⋮ A nondegenerate penalized likelihood estimator for variance parameters in multilevel models ⋮ Selection of Prior for the Variance Component and Approximations for Posterior Moments in the Fay-Herriot Model ⋮ Posterior propriety for hierarchical models with log-likelihoods that have norm bounds ⋮ Modeling Random Effects Using Global–Local Shrinkage Priors in Small Area Estimation

Uses Software

• MLwiN
• BayesDA

Cites Work

• Estimation of the mean of a multivariate normal distribution
• An adjusted maximum likelihood method for solving small area estimation problems
• The Efficiency of Logistic Regression Compared to Normal Discriminant Analysis
• Hierarchical Poisson Regression Modeling
• Parametric Empirical Bayes Inference: Theory and Applications
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