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Statistics
A Journal of Theoretical and Applied Statistics
Volume 41, 2007 - Issue 1
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Original Articles

Parametric robust inference about regression parameters for the correlation coefficient

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Pages 1-9 | Received 09 Jan 2006, Published online: 12 Mar 2007
 

Abstract

This article establishes a robust likelihood function about regression parameters for the correlation coefficients modeled in a generalized linear model fashion. The validity of the proposed likelihood requires no knowledge of the true underlying distributions, so long as they have finite fourth moments. The efficacy of the robust methodology is shown via simulations. The asymptotic variance of the maximum-likelihood estimate and the empirical error probabilities of the resultant robust likelihood ratio test are specifically exhibited.

Acknowledgements

The authors would like to thank the two referees for their valuable suggestions and comments. This work is partly supported by Grant NSC 95-2118-M-008-002 of National Science Council, Taiwan, R.O.C.

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