Improving the James-Stein estimator using the Stein variance estimator

DOI10.1016/0167-7152(94)90049-3zbMath0801.62059OpenAlexW2054897625MaRDI QIDQ1332901

J. Calvin Berry

Publication date: 5 September 1994

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

Full work available at URL: https://doi.org/10.1016/0167-7152(94)90049-3

zbMATH Keywords

James-Stein estimatorshrinkage estimatordominationStein variance estimatormultivariate normal mean vectorpositive part versions

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07)

Related Items (10)

Shrinkage confidence procedures ⋮ ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION ⋮ Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model ⋮ Applications of Improved Variance Estimators in a Multivariate Normal Mean Vector Estimation ⋮ All admissible linear estimators of a regression coefficient under a balanced loss function ⋮ Fractionally-supervised classification ⋮ Stein estimation -- a review ⋮ An Appreciation of Balanced Loss Functions Via Regret Loss ⋮ Inadmissibility of the Stein-rule estimator under the balanced loss function ⋮ On the use of the Stein variance estimator in the double \(k\) -class estimator when each individual regression coefficient is estimated

Cites Work

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• Estimation of the mean of a multivariate normal distribution
• Proper Bayes minimax estimators of the multivariate normal mean vector for the case of common unknown variances
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution

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