THE SMALL SAMPLE PROPERTIES OF THE PRINCIPAL COMPONENTS ESTIMATOR FOR REGRESSION COEFFICIENTS

DOI10.1081/STA-120002651zbMath1008.62627MaRDI QIDQ4540720

Ming Lin, Lai-Sheng Wei

Publication date: 28 July 2002

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Mathematics Subject Classification ID

Linear regression; mixed models (62J05)

Related Items (4)

Adaptive unified biased estimators of parameters in linear model ⋮ A Summary of Some Research on PC and Bayesian PC Criterion in China ⋮ The small sample properties of the restricted principal component regression estimator in linear regression model ⋮ Comparisons of the \(r\)-\(k\) class estimator to the ordinary least squares estimator under the Pitman's closeness criterion

Cites Work

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• Mixed regression estimator under misspecification
• The Pitman comparison of unbiased linear estimators
• The Stein paradox in the sense of the Pitman measure of closeness
• A Comparison of james–sten regression with least squares in the pitman nearness sense
• Comparison of Linear Estimators Using Pitman's Measure of Closeness
• The pitman nearness criterion and its determination

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