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March, 1988 Covariance Hypotheses Which are Linear in Both the Covariance and the Inverse Covariance
Soren Tolver Jensen
Ann. Statist. 16(1): 302-322 (March, 1988). DOI: 10.1214/aos/1176350707

Abstract

It is proved in this paper that covariance hypotheses which are linear in both the covariance and the inverse covariance are products of models each of which consists of either (i) independent identically distributed random vectors which have a covariance with a real, complex or quaternion structure or (ii) independent identically distributed random vectors with a parametrization of the covariance which is given by means of the Clifford algebra. The models (i) are well known. For models (ii) we have found, under the assumption that the distribution is normal, the exact distributions of the maximum likelihood estimates and the likelihood ratio test statistics.

Citation

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Soren Tolver Jensen. "Covariance Hypotheses Which are Linear in Both the Covariance and the Inverse Covariance." Ann. Statist. 16 (1) 302 - 322, March, 1988. https://doi.org/10.1214/aos/1176350707

Information

Published: March, 1988
First available in Project Euclid: 12 April 2007

zbMATH: 0653.62042
MathSciNet: MR924873
Digital Object Identifier: 10.1214/aos/1176350707

Subjects:
Primary: 62H05
Secondary: 62H10, 62H15, 62J10

Rights: Copyright © 1988 Institute of Mathematical Statistics

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Vol.16 • No. 1 • March, 1988
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