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July, 1975 How Much Do Gauss-Markov and Least Square Estimates Differ? A Coordinate-Free Approach
Shelby J. Haberman
Ann. Statist. 3(4): 982-990 (July, 1975). DOI: 10.1214/aos/1176343201

Abstract

A simple expression is developed for the difference between the least squares and minimum variance linear unbiased estimators obtained in linear models in which the covariance operator of the observation vector is nonsingular. Bounds and series expansion for this difference are obtained, and bounds for the efficiency of least squares estimates are also obtained.

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Shelby J. Haberman. "How Much Do Gauss-Markov and Least Square Estimates Differ? A Coordinate-Free Approach." Ann. Statist. 3 (4) 982 - 990, July, 1975. https://doi.org/10.1214/aos/1176343201

Information

Published: July, 1975
First available in Project Euclid: 12 April 2007

zbMATH: 0311.62031
MathSciNet: MR378269
Digital Object Identifier: 10.1214/aos/1176343201

Subjects:
Primary: 62J05
Secondary: 62J10

Keywords: efficiency , Gauss-Markov estimates , least squares , linear models

Rights: Copyright © 1975 Institute of Mathematical Statistics

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Vol.3 • No. 4 • July, 1975
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