A comparison of stein-like procedures for estimating linear regression models with multicollinear data

DOI10.1080/03610929408831333zbMath0825.62164OpenAlexW1980536843MaRDI QIDQ4843814

Dennis Oberhelman, K. R. Kadiyala

Publication date: 17 August 1995

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

Full work available at URL: https://doi.org/10.1080/03610929408831333

zbMATH Keywords

maximum likelihoodprincipal components regressionStein positive-rule estimator

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items

Applied regression analysis bibliography update 1994-97

Uses Software

• SAS
• SAS/STAT

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Minimax multiple shrinkage estimation
• On the concept of non-significant functions and its implications for regression analysis
• Estimation of the mean of a multivariate normal distribution
• Improved prediction in the presence of multicollinearity
• On Truncation of Shrinkage Estimators in Simultaneous Estimation of Normal Means
• A Simulation of Biased Estimation and Subset Selection Regression Techniques
• Collinearity and Optimal Restrictions on Regression Parameters for Estimating Responses
• Improved Estimators for Coefficients in Linear Regression
• The optimal set of principal component restrictions on a least-squares regression