On the use of the Stein variance estimator in the double \(k\) -class estimator when each individual regression coefficient is estimated

DOI10.1007/s00362-002-0137-4zbMath1010.62061OpenAlexW2034234846MaRDI QIDQ1871693

Akio Namba

Publication date: 4 May 2003

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

Full work available at URL: https://doi.org/10.1007/s00362-002-0137-4

zbMATH Keywords

tablesmean squared errordouble k-class estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05)

Related Items (1)

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

Cites Work

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• Further improving the Stein-rule estimator using the Stein variance estimator in a misspecified linear regression model
• Improving the James-Stein estimator using the Stein variance estimator
• Minimum mean squared error estimation of each individual coefficient in a linear regression model
• Inadmissibility of the usual estimator for the variance of a normal distribution with unknown mean
• The exact general fomulae for the moments and the MSE dominance of the Stein-rule and positive-part Stein-rule estimators.
• On an adjustment of degrees of freedom in the minimim mean squared error ertimator
• The Minimum Mean Square Error Linear Estimator and Ridge Regression
• Double k-Class Estimators of Coefficients in Linear Regression
• Precision of individual estimators in simultaneous estimation of parameters
• ON THE USE OF THE STEIN VARIANCE ESTIMATOR IN THE DOUBLE k-CLASS ESTIMATOR IN REGRESSION

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