Improved set estimators for the coefficients of a linear model when the error distribution is spherically symmetric with unknown variances

DOI10.2307/3314735zbMath0675.62023OpenAlexW2128006656MaRDI QIDQ3830354

Jeesen Chen, Jiunn Tzon Hwang

Publication date: 1988

Published in: Canadian Journal of Statistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.2307/3314735

zbMATH Keywords

James-Stein estimatorlinear modeluniform distributioncoverage probabilitydouble-exponential distributionmultivariate t-distributionnormal errorJames-Stein confidence setsspherically symmetric error

Mathematics Subject Classification ID

Parametric tolerance and confidence regions (62F25) Ridge regression; shrinkage estimators (Lasso) (62J07) Central limit and other weak theorems (60F05)

Related Items (2)

Improved point and confidence interval estimators of mean response in simulation when control variates are used ⋮ Confidence sets centered at James-Stein estimators. A surprise concerning the unknown-variance case

Cites Work

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• Improved confidence sets for the coefficients of a linear model with spherically symmetric errors
• Employing vague prior information in the construction of confidence sets
• A robust generalized Bayes estimator and confidence region for a multivariate normal mean
• Minimax confidence sets for the mean of a multivariate normal distribution
• Empirical Bayes Confidence Sets for the Mean of a Multivariate Normal Distribution
• Elliptically Symmetric Distributions: A Review and Bibliography
• Some properties of mutivariate distributions with pdf's constant on ellipsoids
• Bayesian and Non-Bayesian Analysis of the Regression Model with Multivariate Student-t Error Terms
• Student's t-Test Under Symmetry Conditions
• MULTI-FACTOR DESIGNS OF FIRST ORDER

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