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June, 1984 Estimation for the Multivariate Errors-in-Variables Model with Estimated Error Covariance Matrix
Yasuo Amemiya, Wayne A. Fuller
Ann. Statist. 12(2): 497-509 (June, 1984). DOI: 10.1214/aos/1176346502

Abstract

The errors-in-variables model in which the unobserved true values satisfy multiple linear restrictions is considered. Under the assumptions that the unobservable true values are normally distributed and that an estimator of the covariance matrix of the measurement error is available, the maximum likelihood estimators are derived. The limiting properties of the estimators are obtained for a wide range of assumptions, including the assumption of fixed true values.

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Yasuo Amemiya. Wayne A. Fuller. "Estimation for the Multivariate Errors-in-Variables Model with Estimated Error Covariance Matrix." Ann. Statist. 12 (2) 497 - 509, June, 1984. https://doi.org/10.1214/aos/1176346502

Information

Published: June, 1984
First available in Project Euclid: 12 April 2007

zbMATH: 0543.62042
MathSciNet: MR740908
Digital Object Identifier: 10.1214/aos/1176346502

Subjects:
Primary: 62J99
Secondary: 62F10, 62F12, 62H12, 62H25

Rights: Copyright © 1984 Institute of Mathematical Statistics

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Vol.12 • No. 2 • June, 1984
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