MSE dominance of the positive-part shrinkage estimator when each individual regression coefficient is estimated

DOI10.1007/S00362-014-0586-6zbMath1312.62094OpenAlexW1975396838MaRDI QIDQ2340390

Akio Namba

Publication date: 16 April 2015

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

Full work available at URL: https://doi.org/10.1007/s00362-014-0586-6

zbMATH Keywords

mean squared errorshrinkage estimatordominancepre-testpositive-part estimator

Mathematics Subject Classification ID

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

Cites Work

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• Small sample properties of a ridge regression estimator when there exist omitted variables
• Dominance of the positive-part version of the James-Stein estimator
• Minimum mean squared error estimation of each individual coefficient in a linear regression model
• PMSE dominance of the positive-part shrinkage estimator in a regression model when relevant regressors are omitted.
• On the sampling distribution of improved estimators for coefficients in linear regression
• On the use of the Stein variance estimator in the double \(k\) -class estimator when each individual regression coefficient is estimated
• The exact general fomulae for the moments and the MSE dominance of the Stein-rule and positive-part Stein-rule estimators.
• Risk performance of a pre-test ridge regression estimator under the LINEX loss function when each individual regression coefficient is estimated
• Precision of individual estimators in simultaneous estimation of parameters
• A Family of Minimax Estimators of the Mean of a Multivariate Normal Distribution
• Stein's Estimation Rule and Its Competitors--An Empirical Bayes Approach

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