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March, 1981 Tests for the Independence Between Two Seemingly Unrelated Regression Equations
Takeaki Kariya
Ann. Statist. 9(2): 381-390 (March, 1981). DOI: 10.1214/aos/1176345403

Abstract

When the error terms in two different regression equations are correlated, Zellner proposed an alternative estimator for the coefficients of each equation based on an estimated covariance matrix between the two error terms. However, since an estimated covariance matrix is used, the OLSE seems better than Zellner's estimator when the correlation of the two equations is close enough to zero. This paper considers the problem of testing the independence between two regression equations and derives a locally best invariant test for a one-sided alternative hypothesis and a locally best unbiased and invariant test for a two-sided alternative.

Citation

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Takeaki Kariya. "Tests for the Independence Between Two Seemingly Unrelated Regression Equations." Ann. Statist. 9 (2) 381 - 390, March, 1981. https://doi.org/10.1214/aos/1176345403

Information

Published: March, 1981
First available in Project Euclid: 12 April 2007

zbMATH: 0474.62067
MathSciNet: MR606621
Digital Object Identifier: 10.1214/aos/1176345403

Subjects:
Primary: 62H15
Secondary: 62F05 , 62J05

Keywords: Correlation , Invariance , locally best test , seemingly unrelated regression

Rights: Copyright © 1981 Institute of Mathematical Statistics

Vol.9 • No. 2 • March, 1981
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