Minimum mean squared error estimation of each individual coefficient in a linear regression model

DOI10.1016/S0378-3758(96)00180-2zbMath0886.62067WikidataQ126352560 ScholiaQ126352560MaRDI QIDQ1367670

Kazuhiro Ohtani

Publication date: 10 May 1998

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

zbMATH Keywords

Stein-rule estimatorsminimum mean squared error estimatorindividual regression coefficientsMSE dominance

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05) Monte Carlo methods (65C05)

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Cites Work

• Minimum mean square error estimation in linear regression
• The exact general fomulae for the moments and the MSE dominance of the Stein-rule and positive-part Stein-rule estimators.
• The Minimum Mean Square Error Linear Estimator and Ridge Regression
• Simulation and Extension of a Minimum Mean Squared Error Estimator in Comparison with Stein's
• Precision of individual estimators in simultaneous estimation of parameters
• On the minimum mean squared error estimators in a regression model
• Exact small sample properties of an operational variant of the minimum mean squared error estimator
• Comparison of operational variants of Best homogeneous and heterogeneous estimators in linear regression
• Efficient Estimation of the Lorenz Curve and Associated Inequality Measures from Grouped Observations
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